Health monitoring appliance

ABSTRACT

A heart monitoring system for a person includes one or more wireless nodes; and a wearable appliance in communication with the one or more wireless nodes, the appliance monitoring vital signs.

This application is a continuation of U.S. application Ser. No.13/488,351 filed Jun. 4, 2012, which in turn is a continuation-in-partof U.S. application Ser. No. 13/337,217 filed Dec. 6, 2011, which is acontinuation of U.S. application Ser. No. 11/433,900 filed May 12, 2006,and U.S. application Ser. No. 12/426,232 filed Apr. 18, 2009, thecontents of which are incorporated by reference.

BACKGROUND

This invention relates generally to methods and apparatus for monitoringpatients.

Conventionally, the monitoring of a patient such as in an intensive careunit of a hospital has required vigilant surveillance by one or morenurses. More recently, monitoring means have been utilized in the formof electrical monitoring and recording devices which are connected tothe patient by suitable electrical wires. During surgical operations andduring their stay in the ICU (Intensive Care Unit), patients areattached by cables to the monitoring or treatment equipment. Cabling,however, complicates the treatment process in many ways; for instance,cables obstruct nursing procedures and complicate transfers, as theyhave to be attached and detached. Such conventional devices haverequired that the patient's bed be made electrically shockproof. The useof such wiring limits the mobility of the patient and conventionally hasrequired that the patient remain in the shockproof bed. Because of thehigh cost of the equipment and the installation, the use thereof hasbeen primarily limited to intensive care units of hospitals and, thus,such monitoring has not been readily available in connection with lessserious patient problems.

U.S. Pat. No. 3,212,496 discloses a molecular physiological monitoringsystem wherein the voltage produced by the heart in the functioningthereof in sensed and transmitted to an EKG receiver and recording ordisplay device. In Preston, the transducer system is implantedsubcutaneously or externally.

U.S. Pat. No. 3,943,918 discloses a throwaway, one-time use signalsensing and telemetric transmitting device for use such as in the careof medical patients requiring a monitoring of a physiological functionsuch as the cardiac function of the patient. The device includesone-time use self-powering battery means, adhesive means for attachmentof the device to the patient and electrodes for sensing thephysiological functioning. A disposable cover is removed to expose theadhesive means and the battery means are actuated to power the device atthe time of use. The radio frequency transmitted signal is received on asuitable radio telemetry receiver for monitoring and recording asdesired.

SUMMARY

In one aspect, a monitoring system includes one or more wireless nodescommunicating over an aeronautical mobile telemetry (AMT) band; and awearable appliance in communication with the one or more wireless nodesto capture a patient vital sign.

In another aspect, a monitoring system for a person includes one or morewireless nodes; and a wearable appliance in communication with the oneor more wireless nodes, the appliance continuously monitoring vitalsign. Other implementations can monitor heart rate, heart ratevariability, respiratory rate, fluid status, posture and activity.

In yet another aspect, a monitoring system for a person includes one ormore wireless nodes forming a wireless network and a wearable appliancehaving a sound transducer coupled to the wireless transceiver; and aheart disease recognizer coupled to the sound transducer to determinecardiovascular health and to transmit heart sound over the wirelessnetwork to a remote listener if the recognizer identifies acardiovascular problem. The heart sound being transmitted may becompressed to save transmission bandwidth.

In a further aspect, a monitoring system for a person includes one ormore wireless nodes; and a wristwatch having a wireless transceiveradapted to communicate with the one or more wireless nodes; and anaccelerometer to detect a dangerous condition and to generate a warningwhen the dangerous condition is detected.

In another aspect, a monitoring system for a person includes one or morewireless nodes forming a wireless network; and a wearable appliancehaving a wireless transceiver adapted to communicate with the one ormore wireless nodes; and a heartbeat detector coupled to the wirelesstransceiver. The system may also include an accelerometer to detect adangerous condition such as a falling condition and to generate awarning when the dangerous condition is detected.

In another aspect, a monitoring system for a person includes one or morewireless bases; and a cellular telephone having a wireless transceiveradapted to communicate with the one or more wireless bases; and anaccelerometer to detect a dangerous condition and to generate a warningwhen the dangerous condition is detected.

In yet another aspect, a monitoring system includes one or more camerasto determine a three dimensional (3D) model of a person; means to detecta dangerous condition based on the 3D model; and means to generate awarning when the dangerous condition is detected.

In another aspect, a method to detect a dangerous condition for aninfant includes placing a pad with one or more sensors in the infant'sdiaper; collecting infant vital parameters; processing the vitalparameter to detect SIDS onset; and generating a warning.

Implementations of the above aspect may include one or more of thefollowing. The system wirelessly monitors parameters such as RR(respiratory rate), SpO2 (oxygen saturation), ECG (electrocardiogram),HR (heart rate), core temperature (inside the heart) and peripheraltemperature (on top of the instep), CI (cardiac output index, CO/m2),systematic pressures (SSAP, systematic systolic arterial pressure; SDAP,systematic diastolic arterial pressure; SMAP, systematic mean arterialpressure), CVP (central venous pressure), pulmonary pressures (PSAP,pulmonary systolic arterial pressure; PDAP, pulmonary diastolic arterialpressure; PMAP, pulmonary mean arterial pressure), svO2 (oxygensaturation in the lung artery), ETCO2 (outcoming carbon dioxide), FIO(ingoing oxygen), diuretics, the patient's weight, fluid balance(ingoing and outcoming fluids) and EEG. The device can be a wristwatchthat determines position based on triangulation. The wristwatchdetermines position based on RF signal strength and RF signal angle. Aswitch detects a confirmatory signal from the person. The confirmatorysignal includes a head movement, a hand movement, or a mouth movement.The confirmatory signal includes the person's voice. A processor in thesystem executes computer readable code to transmit a help request to aremote computer. The code can encrypt or scramble data for privacy. Theprocessor can execute voice over IP (VOIP) code to allow a user and aremote person to audibly communicate with each other. The voicecommunication system can include Zigbee VOIP or Bluetooth VOIP or 802.XXVOIP. The remote person can be a doctor, a nurse, a medical assistant,or a caregiver. The system includes code to store and analyze patientinformation. The patient information includes medicine taking habits,eating and drinking habits, sleeping habits, or excise habits. A patientinterface is provided on a user computer for accessing information andthe patient interface includes in one implementation a touch screen;voice-activated text reading; and one touch telephone dialing. Theprocessor can execute code to store and analyze information relating tothe person's ambulation. A global positioning system (GPS) receiver canbe used to detect movement and where the person falls. The system caninclude code to map the person's location onto an area for viewing. Thesystem can include one or more cameras positioned to capture threedimensional (3D) video of the patient; and a server coupled to the oneor more cameras, the server executing code to detect a dangerouscondition for the patient based on the 3D video and allow a remote thirdparty to view images of the patient when the dangerous condition isdetected.

Advantages of the invention may include one or more of the following.The system eliminates cables attaching patient monitoring sensors tomonitoring devices without disturbing and obstructing nursing staff.Vital parameters, such as blood pressure, electrocardiography (ECG),respiration rate, heart rate and temperature, from patient who is incritical condition are measured all the time. Wireless connectionsenable free redeployment of patient between separate units and allowfree movement of the patient. Wireless connections will offer quick andeasy way to redeploy the patient, e.g., from an operating room to anintensive care unit (ICU) and make the movement of patient more easier.

The system is highly reliable and is at least as reliable as wiredtechniques. Interference is reduced by operating at a differentfrequency than Bluetooth and 2.45 GHz WLAN. The system avoidsinterference from surgical knives, mobile phones and even microwaveovens through error correction and redundant transmission within ahospital. The absence of cables around patients will improve the workingconditions of nursing staff, and enhance their efficiency. When patientsarrive at the hospital, sensors will be attached to them and removed asthey check out. All patient information, including personal data,laboratory test results, patient monitor signals etc., will betransferred to one single database. During their stay, patients remainconnected to the hospital network and can either move freely or betransferred anywhere in the hospital. Relevant nursing staff will beable to examine patient information via a PDA, for example, anywhere inthe hospital. Additional information can be sent outside the hospital toa consulting doctor through a mobile phone, PDA or via e-mail.

The device can be applied in the manner of a conventional bandage to thepatient's body without complicated or extensive preparation of thepatient. As the device is extremely simple and economical ofconstruction, it may be utilized as a one-time use, throwaway devicewhich permits high mobility of the patient while yet providingcontinuous monitoring of the sensed physiological function. The systemfor non-invasively and continually monitors a subject's arterial bloodpressure, with reduced susceptibility to noise and subject movement, andrelative insensitivity to placement of the apparatus on the subject. Thesystem does not need frequent recalibration of the system while in useon the subject.

In particular, it allows patients to conduct a low-cost, comprehensive,real-time monitoring of their blood pressure. Using the web servicessoftware interface, the invention then avails this information tohospitals, home-health care organizations, insurance companies,pharmaceutical agencies conducting clinical trials and otherorganizations. Information can be viewed using an Internet-basedwebsite, a personal computer, or simply by viewing a display on themonitor. Data measured several times each day provide a relativelycomprehensive data set compared to that measured during medicalappointments separated by several weeks or even months. This allows boththe patient and medical professional to observe trends in the data, suchas a gradual increase or decrease in blood pressure, which may indicatea medical condition. The invention also minimizes effects of white coatsyndrome since the monitor automatically makes measurements withbasically no discomfort; measurements are made at the patient's home orwork, rather than in a medical office.

The wearable appliance is small, easily worn by the patient duringperiods of exercise or day-to-day activities, and non-invasivelymeasures blood pressure can be done in a matter of seconds withoutaffecting the patient. An on-board or remote processor can analyze thetime-dependent measurements to generate statistics on a patient's bloodpressure (e.g., average pressures, standard deviation, beat-to-beatpressure variations) that are not available with conventional devicesthat only measure systolic and diastolic blood pressure at isolatedtimes.

The wearable appliance provides an in-depth, cost-effective mechanism toevaluate a patient's cardiac condition. Certain cardiac conditions canbe controlled, and in some cases predicted, before they actually occur.Moreover, data from the patient can be collected and analyzed while thepatient participates in their normal, day-to-day activities.

In cases where the device has fall detection in addition to bloodpressure measurement, other advantages of the invention may include oneor more of the following. The system provides timely assistance andenables elderly and disabled individuals to live relatively independentlives. The system monitors physical activity patterns, detects theoccurrence of falls, and recognizes body motion patterns leading tofalls. Continuous monitoring of patients is done in an accurate,convenient, unobtrusive, private and socially acceptable manner since acomputer monitors the images and human involvement is allowed only underpre-designated events. The patient's privacy is preserved since humanaccess to videos of the patient is restricted: the system only allowshuman viewing under emergency or other highly controlled conditionsdesignated in advance by the user. When the patient is healthy, peoplecannot view the patient's video without the patient's consent. Only whenthe patient's safety is threatened would the system provide patientinformation to authorized medical providers to assist the patient. Whenan emergency occurs, images of the patient and related medical data canbe compiled and sent to paramedics or hospital for proper preparationfor pick up and check into emergency room.

The system allows certain designated people such as a family member, afriend, or a neighbor to informally check on the well-being of thepatient. The system is also effective in containing the spiraling costof healthcare and outpatient care as a treatment modality by providingremote diagnostic capability so that a remote healthcare provider (suchas a doctor, nurse, therapist or caregiver) can visually communicatewith the patient in performing remote diagnosis. The system allowsskilled doctors, nurses, physical therapists, and other scarce resourcesto assist patients in a highly efficient manner since they can do themajority of their functions remotely.

Additionally, a sudden change of activity (or inactivity) can indicate aproblem. The remote healthcare provider may receive alerts over theInternet or urgent notifications over the phone in case of such suddenaccident indicating changes. Reports of health/activity indicators andthe overall well-being of the individual can be compiled for the remotehealthcare provider. Feedback reports can be sent to monitored subjects,their designated informal caregiver and their remote healthcareprovider. Feedback to the individual can encourage the individual toremain active. The content of the report may be tailored to the targetrecipient's needs, and can present the information in a formatunderstandable by an elder person unfamiliar with computers, via anappealing patient interface. The remote healthcare provider will haveaccess to the health and well-being status of their patients withoutbeing intrusive, having to call or visit to get such informationinterrogatively. Additionally, remote healthcare provider can receive areport on the health of the monitored subjects that will help themevaluate these individuals better during the short routine check-upvisits. For example, the system can perform patient behavior analysissuch as eating/drinking/smoke habits and medication compliance, amongothers.

The patient's home equipment is simple to use and modular to allow forthe accommodation of the monitoring device to the specific needs of eachpatient. Moreover, the system is simple to install. Regular monitoringof the basic wellness parameters provides significant benefits inhelping to capture adverse events sooner, reduce hospital admissions,and improve the effectiveness of medications, hence, lowering patientcare costs and improving the overall quality of care. Suitable users forsuch systems are disease management companies, health insurancecompanies, self-insured employers, medical device manufacturers andpharmaceutical firms.

The system reduces costs by automating data collection and compliancemonitoring, and hence reduce the cost of nurses for hospital and nursinghome applications. At-home vital signs monitoring enables reducedhospital admissions and lower emergency room visits of chronic patients.Operators in the call centers or emergency response units get highquality information to identify patients that need urgent care so thatthey can be treated quickly, safely, and cost effectively. The Web basedtools allow easy access to patient information for authorized partiessuch as family members, neighbors, physicians, nurses, pharmacists,caregivers, and other affiliated parties to improve the Quality of Carefor the patient.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A illustrates an exemplary system for monitoring a person.

FIG. 1B a schematic representation of a patient provided with a signalsensing and telemetric transmitting device embodying the invention inconnection with the transmitting of physiologic signals to a suitablereceiver, monitor, and recorder.

FIG. 1C is a perspective view of a monitoring patch, pad or band-aidready to be worn by a patient for transmitting vital signs.

FIG. 1D shows an exemplary module with redundant transceivers andredundant antennas.

FIG. 1E shows another exemplary module with redundant transceivers andredundant antennas.

FIG. 1F shows a multi-band frequency hopping embodiment.

FIG. 1G shows a wideband bed antenna embodiment.

FIG. 1H shows a bed receiver with large antenna where the receiver iswired to hospital monitoring equipment.

FIG. 1I shows a multi-band system that transmits over RF and opticalbands.

FIG. 1J shows a multi-band system that transmits over ultra-wideban,Zigbee, WiFi and optical bands.

FIG. 1K shows mesh networking that transmits over various wireless andoptical protocols in a node to node basis to avoid a jammed node forenhanced reliability.

FIG. 1L shows exemplary low power cells for patient telemetry.

FIG. 1M shows an embodiment with scheduled transmissions.

FIG. 1N shows an exemplary high gain parabolic bed antenna.

FIG. 2A illustrates a process for determining three dimensional (3D)detection.

FIG. 2B shows an exemplary calibration sheet.

FIG. 3 illustrates a process for detecting falls.

FIG. 4 illustrates a process for detecting facial expressions.

FIG. 5 illustrates an exemplary process for determining and gettingassistance for a patient or user.

FIG. 6A shows an exemplary wrist-watch based assistance device.

FIG. 6B shows an exemplary mesh network working with the wearableappliance of FIG. 6A.

FIG. 7 shows an exemplary mesh network in communication with thewrist-watch device of FIG. 6.

FIGS. 8-14 show various exemplary wearable appliances to monitor apatient.

FIGS. 15A-15B show exemplary systems for performing patient monitoring.

FIG. 15C shows an exemplary interface to monitor a plurality of persons.

FIG. 15D shows an exemplary dash-board that provides summary informationon the status of a plurality of persons.

FIG. 15E shows an exemplary multi-station vital parameter user interfacefor a professional embodiment.

FIG. 15F shows an exemplary trending pattern display.

FIGS. 16A-16B show exemplary blood pressure determination processes.

DESCRIPTION

FIG. 1A shows an exemplary patient monitoring system. The system canoperate in a home, a nursing home, or a hospital. In this system, one ormore mesh network appliances 8 are provided to enable wirelesscommunication in the home monitoring system. Appliances 8 in the meshnetwork can include home security monitoring devices, door alarm, windowalarm, home temperature control devices, fire alarm devices, amongothers. Appliances 8 in the mesh network can be one of multiple portablephysiological transducer, such as a blood pressure monitor, heart ratemonitor, weight scale, thermometer, spirometer, single or multiple leadelectrocardiograph (ECG), a pulse oxymeter, a body fat monitor, acholesterol monitor, a signal from a medicine cabinet, a signal from adrug container, a signal from a commonly used appliance such as arefrigerator/stove/oven/washer, or a signal from an exercise machine,such as a heart rate. As will be discussed in more detail below, oneappliance is a patient monitoring device that can be worn by the patientand includes a single or bi-directional wireless communication link,generally identified by the bolt symbol in FIG. 1, for transmitting datafrom the appliances 8 to the local hub or receiving station or basestation server 20 by way of a wireless radio frequency (RF) link using aproprietary or non-proprietary protocol. For example, within a house, auser may have mesh network appliances that detect window and doorcontacts, smoke detectors and motion sensors, video cameras, key chaincontrol, temperature monitors, CO and other gas detectors, vibrationsensors, and others. A user may have flood sensors and other detectorson a boat. An individual, such as an ill or elderly grandparent, mayhave access to a panic transmitter or other alarm transmitter. Othersensors and/or detectors may also be included. The user may registerthese appliances on a central security network by entering theidentification code for each registered appliance/device and/or system.The mesh network can be Zigbee network or 802.15 network. More detailsof the mesh network is shown in FIG. 7 and discussed in more detailbelow.

A plurality of monitoring cameras 10 may be placed in variouspredetermined positions in a home of a patient 30. The cameras 10 can bewired or wireless. For example, the cameras can communicate overinfrared links or over radio links conforming to the 802X (e.g. 802.11A,802.11B, 802.11G, 802.15) standard or the Bluetooth standard to a basestation/server 20 may communicate over various communication links, suchas a direct connection, such a serial connection, USB connection,Firewire connection or may be optically based, such as infrared orwireless based, for example, home RF, IEEE standard 802.11a/b, Bluetoothor the like. In one embodiment, appliances 8 monitor the patient andactivates the camera 10 to capture and transmit video to an authorizedthird party for providing assistance should the appliance 8 detects thatthe user needs assistance or that an emergency had occurred.

The base station/server 20 stores the patient's ambulation pattern andvital parameters and can be accessed by the patient's family members(sons/daughters), physicians, caretakers, nurses, hospitals, and elderlycommunity The base station/server 20 may communicate with the remoteserver 200 by DSL, T-1 connection over a private communication networkor a public information network, such as the Internet 100, among others.

The patient 30 may wear one or more wearable patient monitoringappliances such as wrist-watches or clip on devices or electronicjewelry to monitor the patient. One wearable appliance such as awrist-watch includes sensors 40, for example devices for sensing ECG,EKG, blood pressure, sugar level, among others. In one embodiment, thesensors 40 are mounted on the patient's wrist (such as a wristwatchsensor) and other convenient anatomical locations. Exemplary sensors 40include standard medical diagnostics for detecting the body's electricalsignals emanating from muscles (EMG and EOG) and brain (EEG) andcardiovascular system (ECG). Leg sensors can include piezoelectricaccelerometers designed to give qualitative assessment of limb movement.Additionally, thoracic and abdominal bands used to measure expansion andcontraction of the thorax and abdomen respectively. A small sensor canbe mounted on the subject's finger in order to detect blood-oxygenlevels and pulse rate. Additionally, a microphone can be attached tothroat and used in sleep diagnostic recordings for detecting breathingand other noise. One or more position sensors can be used for detectingorientation of body (lying on left side, right side or back) duringsleep diagnostic recordings. Each of sensors 40 can individuallytransmit data to the server 20 using wired or wireless transmission.Alternatively, all sensors 40 can be fed through a common bus into asingle transceiver for wired or wireless transmission. The transmissioncan be done using a magnetic medium such as a floppy disk or a flashmemory card, or can be done using infrared or radio network link, amongothers. The sensor 40 can also include an indoor positioning system oralternatively a global position system (GPS) receiver that relays theposition and ambulatory patterns of the patient to the server 20 formobility tracking.

In one embodiment, the sensors 40 for monitoring vital signs areenclosed in a wrist-watch sized case supported on a wrist band. Thesensors can be attached to the back of the case. For example, in oneembodiment, Cygnus' AutoSensor (Redwood City, Calif.) is used as aglucose sensor. A low electric current pulls glucose through the skin.Glucose is accumulated in two gel collection discs in the AutoSensor.The AutoSensor measures the glucose and a reading is displayed by thewatch.

In another embodiment, EKG/ECG contact points are positioned on the backof the wrist-watch case. In yet another embodiment that providescontinuous, beat-to-beat wrist arterial pulse rate measurements, apressure sensor is housed in a casing with a ‘free-floating’ plunger asthe sensor applanates the radial artery. A strap provides a constantforce for effective applanation and ensuring the position of the sensorhousing to remain constant after any wrist movements. The change in theelectrical signals due to change in pressure is detected as a result ofthe piezoresistive nature of the sensor are then analyzed to arrive atvarious arterial pressure, systolic pressure, diastolic pressure, timeindices, and other blood pressure parameters.

The case may be of a number of variations of shape but can beconveniently made a rectangular, approaching a box-like configuration.The wrist-band can be an expansion band or a wristwatch strap ofplastic, leather or woven material. The wrist-band further contains anantenna for transmitting or receiving radio frequency signals. Thewristband and the antenna inside the band are mechanically coupled tothe top and bottom sides of the wrist-watch housing. Further, theantenna is electrically coupled to a radio frequency transmitter andreceiver for wireless communications with another computer or anotheruser. Although a wrist-band is disclosed, a number of substitutes may beused, including a belt, a ring holder, a brace, or a bracelet, amongother suitable substitutes known to one skilled in the art. The housingcontains the processor and associated peripherals to provide thehuman-machine interface. A display is located on the front section ofthe housing. A speaker, a microphone, and a plurality of push-buttonswitches and are also located on the front section of housing. Aninfrared LED transmitter and an infrared LED receiver are positioned onthe right side of housing to enable the watch to communicate withanother computer using infrared transmission.

In another embodiment, the sensors 40 are mounted on the patient'sclothing. For example, sensors can be woven into a single-piece garment(an undershirt) on a weaving machine. A plastic optical fiber can beintegrated into the structure during the fabric production processwithout any discontinuities at the armhole or the seams. Aninterconnection technology transmits information from (and to) sensorsmounted at any location on the body thus creating a flexible “bus”structure. T-Connectors—similar to “button clips” used in clothing—areattached to the fibers that serve as a data bus to carry the informationfrom the sensors (e.g., EKG sensors) on the body. The sensors will pluginto these connectors and at the other end similar T-Connectors will beused to transmit the information to monitoring equipment or personalstatus monitor. Since shapes and sizes of humans will be different,sensors can be positioned on the right locations for all patients andwithout any constraints being imposed by the clothing. Moreover, theclothing can be laundered without any damage to the sensors themselves.In addition to the fiber optic and specialty fibers that serve assensors and data bus to carry sensory information from the wearer to themonitoring devices, sensors for monitoring the respiration rate can beintegrated into the structure.

In another embodiment, instead of being mounted on the patient, thesensors can be mounted on fixed surfaces such as walls or tables, forexample. One such sensor is a motion detector. Another sensor is aproximity sensor. The fixed sensors can operate alone or in conjunctionwith the cameras 10. In one embodiment where the motion detectoroperates with the cameras 10, the motion detector can be used to triggercamera recording. Thus, as long as motion is sensed, images from thecameras 10 are not saved. However, when motion is not detected, theimages are stored and an alarm may be generated. In another embodimentwhere the motion detector operates stand alone, when no motion issensed, the system generates an alarm.

The server 20 also executes one or more software modules to analyze datafrom the patient. A module 50 monitors the patient's vital signs such asECG/EKG and generates warnings should problems occur. In this module,vital signs can be collected and communicated to the server 20 usingwired or wireless transmitters. In one embodiment, the server 20 feedsthe data to a statistical analyzer such as a neural network which hasbeen trained to flag potentially dangerous conditions. The neuralnetwork can be a back-propagation neural network, for example. In thisembodiment, the statistical analyzer is trained with training data wherecertain signals are determined to be undesirable for the patient, givenhis age, weight, and physical limitations, among others. For example,the patient's glucose level should be within a well-established range,and any value outside of this range is flagged by the statisticalanalyzer as a dangerous condition. As used herein, the dangerouscondition can be specified as an event or a pattern that can causephysiological or psychological damage to the patient. Moreover,interactions between different vital signals can be accounted for sothat the statistical analyzer can take into consideration instanceswhere individually the vital signs are acceptable, but in certaincombinations, the vital signs can indicate potentially dangerousconditions. Once trained, the data received by the server 20 can beappropriately scaled and processed by the statistical analyzer. Inaddition to statistical analyzers, the server 20 can process vital signsusing rule-based inference engines, fuzzy logic, as well as conventionalif-then logic. Additionally, the server can process vital signs usingHidden Markov Models (HMMs), dynamic time warping, or template matching,among others.

Through various software modules, the system reads video sequence andgenerates a 3D anatomy file out of the sequence. The proper bone andmuscle scene structure are created for head and face. A based profilestock phase shape will be created by this scene structure. Every scenewill then be normalized to a standardized viewport.

A module 52 monitors the patient ambulatory pattern and generateswarnings should the patient's patterns indicate that the patient hasfallen or is likely to fall.

FIG. 1B shows one exemplary embodiment hospital wireless monitoringsystem that forms a “medical body area network” (MBAN). In thisembodiment, a physiologic signal sensing and transmitting telemetricdevice generally designated 10 is shown to comprise a device adapted tobe affixed to the chest C of a patient for sensing a physiologicalfunction of the patient such as a cardiac function and transmittingsuitable radio signals R corresponding thereto to a receiver 11 and asuitable monitor and recording device 12. The receiver 11 may beprovided with a suitable antenna 13 for receiving the radio signals R ata location remote from the patient. The receiver may be installed in thesame room with the patient, or at a central surveillance area as desiredwithin the range of the transmitting device 10. The patient may utilizea conventional hospital bed B which need not be electricallyshockproofed and is free to move about within the range of thetransmitter with the device 10 remaining attached to the patient's bodyin the manner of a small adhesive bandage which may preferably be of thenonallergenic type.

As shown in FIG. 1C, device 10 may comprise a block 14 of suitablenonallergenic foam plastic having a nonallergenic adhesive coated frontsurface 15 normally covered by a suitable protective sheet 16.Nonallergenic electrodes 17 project outwardly from the surface 15 and anoptional body of suitable electrically conductive nonallergenic jelly ofconventional form 18 is provided in association with each electrode alsosuitably covered by the sheet 16 prior to use of the device. Eachelectrode illustratively may be formed of silver-silver chloride andcomprise a circular electrode of approximately ¾ inch diameter with theelectrodes being spaced apart approximately 1 inch on center from theblock 14. The device may be stored in a sterile pack for extendedperiods of time within the normal shelf life of the batteries and madeavailable substantially instantaneously for use by the simple removalfrom the sterile pack and removal of the protective cover sheet 16 andmanipulation of the battery actuator 20. An electronic unit 77 containselectronic conditioning circuits and wireless telemetry circuits andrechargeable battery. In one embodiment, the electronic unit 77 isinserted through slots 22 and then slides on rails 20 to make secureelectrical contacts with the electrodes 17. In this manner, theelectronic unit 77 can be securely coupled to the electrodes 17 to makegood electrical contacts thereto. In one embodiment, the electronic unit77 includes an analog front end chip that can sense bio-potentialsignals in; digitized signals out; acquisition (ECG) channels+1 drivenlead; AC and DC Leads Off Detection; Internal Pace Detection Algorithmon 3 leads; and Thoracic Impedance Measurement (internal/external path).

The package cover device 10 is for one time use and is disposed of afteruse. To aid in recycling, the electronic unit 77 is removed prior todisposal of device 10 and is disinfected and recharged for a subsequentuse. In this manner, the system is environmentally friendly whilekeeping cost down at a high level of performance. In one embodiment,prior to use, a protective tape electrically isolating the battery isremoved, and the electronic module 77 is inserted into disposable device10. The electronic module 77 cooperates with rails 20 that connect theunit 77 with body contacts 17-18 that make electrical contact with thepatient.

The recyclable transceiver with the disposable shell can monitor anarray of physiological data, such as temperature, pulse, blood glucoselevel, blood pressure, and respiratory function. One embodiment can useexisting transceivers such as Zigbee, Bluetooth, or WiFi. Thefrequencies for the MBAN network (2360-2400 MHz) can be aeronauticalmobile telemetry (AMT) frequency, for federal radio location tasks, andby amateur radio operators. The bandwidths cover 2360-2400 MHz;2300-2305 MHz and 2395-2400 MHz; 2400-2483.5 MHz; or 5150-5250 MHz—andreside next those now used by Bluetooth devices. In addition, themodifications proposed by the industry representatives would use the2390-2400 MHz range as a secondary MBAN network when the primaryfrequencies interfere with aeronautical industry communications. Byallocating spectrum for medical sensors, patients will avoid havingwireless dead zones interrupt their transmission of vital data todoctors. This spectrum, previously reserved for commercial test pilots,could be used in hospitals, clinics and doctors' offices. Before ahealth care facility could use the 2,360 to 2,390 MHz band, they gothrough a coordination process that considers its actual geographiclocation in the context of actual aeronautical telemetry receiverlocations and actual existing use of the band. Since there arerelatively few aeronautical receive locations and they tend to beclustered-around certain military bases, for example—the majority ofhospitals-around 96 percent-would have access to the entire band.

In one implementation, the 2360-2400 MHz for Medical Body Area Networks(MBAN) can be divided into two subbands:

-   -   In 2360-2390 MHz, devices would be limited to use inside        hospitals, contain electronic means to prevent operation outside        the hospital and be excluded from zones around AMT facilities        using the band unless specifically coordinated with the AMT        facility. Hospitals would be required to register with a        coordinator when MBAN devices are first deployed.    -   In 2390-2400 MHz, devices would be permitted anywhere, such as        in ambulances for monitoring on way to hospitals, in homes to        permit remote monitoring, and anywhere else that electronic        monitoring of patients' vital signs may be desired.

These short-range networks comprise small, low-power sensors that can beplaced on the body to pick up vital data, such as body temperature andrespiratory function. Sensors attach to the body and a local wirelesshub. Hospitals will receive a unique key to activate their portion ofthe band. This key is automatically distributed to MBAN devices in thehospital by the beacon signal, which ensures that the MBAN devicesoperating according to the key are actually located in the hospital atthe time.

One embodiment provides for an 11.5 mile radius exclusion zone toprotect AMT sites. Frequency coordination are used to register alllocations where devices are operating within hospitals in the 2360-2390MHz sub-band. Operation of medical devices within an exclusion zone mustbe pre-coordinated. Conversely, new AMT requirements and mobile AMToperations would have access to accurate information on the location ofhospitals with deployed MBAN devices so that coordination can beaccomplished without any potential for harmful interference.

In one implementation, compliance with in-hospital and exclusion zonelimits can be assured a software key with the controller. The controllercould operate in the 2360-2390 MHz band only if loaded with the softwarekey assigned it by the spectrum coordinator. The individual body-worndevices would be operable only as “slaves” and transmit only if theydetect an authorized controller. Since controllers are professionallyinstalled and configured, individual body-worn devices could not operateoutside the immediate vicinity of a properly authorized controller.

Without the proper coding, both the controller and the body worn deviceswould default to the 2390-2400 MHz band where operation would bepermitted anywhere. Specifically, MBAN devices operating in the2360-2390 MHz sub-band worn outside the hospital setting would beautomatically disabled or could revert to the generally available2390-2400 MHz sub-band if within range of a controller operating withinthe same available sub-band. In another embodiment, cognitivetechnologies including listen-before-talk (LBT), DFS, etc. would permitdevices to avoid channels already in use. This embodiment preventsinterference to others and also prevents interference to the deviceitself from others. A hub device can control MBAN sensors and seamlesslymove devices to another frequency when interference is encountered,protecting both the other user and the integrity of the MBANcommunication. Automatic Power Control (APC) also is likely to beutilized to preserve and extend battery power for these small devices.Another advantage of APC is that the transmitted signal will decreaseautomatically to the minimum required to maintain the communicationslink. This capability will further reduce the interference potential ofMBAN devices wherever they are deployed.

Next, security issues will be addressed. In one embodiment, the systemuses 64 as well as 128-bit AES encryption. The system implementsmultiple layers of security measures to control access tomission-critical systems and networks. These are often the targets thatan attacker attempts to gain unauthorized access to by compromising awireless network and using it as an attack path or vector in to anorganizational network such as a hospital network where the targetsystems reside. In order to defend the target environment, multiplesecurity measures are implemented so that if one measure is defeated byan attacker, additional measures and layers of security remain toprotect the target environment. Measures such as separation of wirelessand wired network segments, strong device and user authenticationmethods, filtering of traffic based on addresses and protocols, securingend-points/stations from unauthorized access, and monitoring andintrusion detection on the wireless and wired segments are examples ofmultiple layers of defense that can be employed to achieve adefense-in-depth design. The wireless networks and wired networks shouldnot be directly connected if possible. For example, a wirelessenvironmental sensing LR-WPAN or equipment monitoring LR-WPAN networkshould not have direct connectivity to the wired healthcare network, butinstead be separated by a device such as a firewall, bastion host, orsecurity gateway to establish a security perimeter that can moreeffectively isolate, segment, and control traffic flows between them.Security features at the upper layer standards and the IEEE lower layerstandards are enabled. Both standards have security services defined intheir specifications. Having security defined at both the higher andlower layers of the protocol stack creates a stronger security solution.

Source node authentication is implemented in order to cryptographicallyverify the identity of a transmitting node. Although a shared NetworkKey will provide a security check for packets utilizing the network,source node authentication can be used by the destination device toverify the identity of the source device. In order to authenticate asource device, a Link Key (end-to-end crypto key) must be generated andused. This key is unique to a pair of devices that are communicatingwith each other and is derived from their respective Master Keys. (Thisis equivalent to the concept of a shared secret or unique session keythat is derived between two entities in order secure data transmittedbetween them.)

One implementation of the security architecture includes securitymechanisms at three layers of the protocol stack—MAC, Network, andApplication. Each layer has services defined for the secure transport oftheir respective frames. The MAC layer is responsible for its ownsecurity processing, but the upper layers determine which security levelto use. When MAC layer integrity protection is employed, the entire MACframe is protected, including the MAC header that contains the hardwaresource and destination addresses. By enabling MAC frame integrity, theMAC layer source address can be authenticated. This measure can counteraddress spoofing attacks and allow a device to more effectively processand compare a received MAC frame against an Access Control List (ACL).Cryptography is based on the use of 128-bit keys and the AES encryptionstandard. Encryption, integrity, and authentication can be applied atthe Application, Network, and MAC layers to secure the frames at each ofthose levels. Master, Link, and Network keys secure transmitted frames.A Network Key is a common key shared among all nodes in a network. Thestandard also specifies an Alternate Network Key as a form of keyrotation that may be employed for key update purposes. At a minimum, anetwork should be secured with the use of a Network Key used by all thedevices to protect all network frames (routing messages, network joinrequests, etc.) and prevent the unauthorized joining and use of thenetwork by illegitimate devices. Link Keys, on the other hand, aresecret session keys used between two communicating devices and areunique to those devices. Devices use their Master Key to generate theLink Key. The manner in which Master, Link and Network Keys aregenerated, stored, processed, and delivered to devices determines theeffectiveness and degree of security of the overall networkimplementation.

All devices within a network recognize and trust exactly one TrustCenter (TC). The TC stores and distributes keys to devices, but it ispreferred to pre-load the keys into the devices directly.) The functionsperformed by the TC are trust management, network management, andconfiguration management.

In addition to configuring a dedicated Coordinator for the network, apredetermined PAN Identifier is used by the Coordinator. The nodes arelimited to joining only the network with the pre-assigned PANIdentifier. Also, the network policy is configured to use the permitjoin access control to restrict device connectivity. Preferably, anout-of-band method is used for loading the cryptographic key(s) onto thedevices. The methods for key management (generation, distribution,updating, revoking, etc.) will vary. Generally, the initial generationand loading of cryptographic keys (e.g. the Master key) will be possiblein three ways. One way is out-of-band: This method entails loading thekey into the device using a mechanism other than through the normalwireless communication channels used for network operation. An examplewould be a serial port on the device through which a key could be loadedwith a cable attachment to the key generation device (such as a laptopor the Trust Center host). Alternatively, in-band method can be usedwhich delivers keys over-the-air through the normal wirelesscommunication channels used for network operation. This is a less securemethod of key delivery because the transmission of the key to a devicejoining the network that has not been pre-configured is unprotected(creating a potential short period of vulnerability). The leastpreferred is factory pre-loaded: This method of key deliver consists ofthe vendor generating and loading the key(s) into the devices at themanufacturing location prior to deliver to the customer. Key values mustsubsequently be conveyed to the customer when they receive theequipment. This approach is the least secure because the vendor hasknowledge of the key values and must also successfully convey theinformation to the customer in a secure manner. Also, as there isexactly one TC in a network, if possible, the address of the TC shouldbe pre-loaded into the node which can be combined with pre-loading ofthe crypto keys.

In an embodiment, the communication of health related informationbetween sensors in a MBAN may be subjected to the security requirementssuch as data confidentiality, data authenticity, data integrity, anddata freshness. The data confidentiality described herein may enable theaccess to the transmitted information by authorized persons (such as thedoctor attending the patient). In an embodiment, the dataconfidentiality can be achieved by encrypting the information beforesending it using a secret key and can be both symmetrically andasymmetrically. The data authenticity described herein may provide ameans for making sure that the information is sent by the claimed sender(such as a doctor or a patient). In an embodiment, a MessageAuthentication Code (MAC3) may be calculated using a shared secret key.The data integrity described herein may enable to determine that theinformation received has not been tampered with any other intermediatesources. In an embodiment, the system may implement security protocolssuch as by verifying the MAC. The data freshness described herein mayguarantee most recent data can be accessed.

One implementation of the security architecture includes securitymechanism that provides secure communication such as by encrypting datausing one or more encryption keys. A configuration security server incommunication with a security manager of the network may provide atemporary secure communication path between the security manager and awireless device of the MBAN network. The cryptographic material andother configuration data can then be transferred between the securitymanager and the wireless devices in the MBAN network via theconfiguration security server.

One implementation of the security architecture includes techniques forsecure communications among MBAN. In response to a packet received at afirst access point of the wireless MBAN from a local end-user destinedto another end-user associated, the packet can be routed via atunnelling protocol such as to provide secure communication in the MBAN.

Next, reliable transmission of critical patient data is discussed. Asdiscussed above, hospital environments can produce a significant amountof electromagnetic noise from surgical knives, mobile phones, microwaveovens, and various actuator devices. The resulting EMI (Electro MagneticInterference) can interfere with the operation of LR-WPAN networks byincreasing the white noise floor and reducing the signal-to-noisequality of transmissions. In one implementation, the MAC layer is basedon the CSMA/CA (Carrier Sense Multiple Access with Collision Avoidance)channel access method in which a station will first listen for an openchannel before transmitting. This is done by sensing the energy level inthe frequency band corresponding to the channel. In an environment withsignificant levels of EMI, the noise floor in the operating frequencyranges of networks can prevent stations from transmitting because the RFenergy threshold level for an open channel has been exceeded.

To address this issue, in one embodiment, a Guaranteed Time Slot (GTS)transmission mode accesses the wireless medium based on regular timeslots assigned to devices by the LR-WPAN Coordinator. GTS mode can beemployed to ensure that devices with critical data to transmit areguaranteed the opportunity to send during a specified time intervalwithout risking a collision with other devices transmitting at the sametime.

Another embodiment uses Frequency Hopping (FH) radio with configurablehopping channels and patterns to avoid RFI from surgical knives andsimilar devices. This type of temporal and frequency diversity approachcan improve EMI immunity in an industrial environment as well as providean additional measure of security if a non-default hopping pattern isused and also changed on a periodic basis.

In another embodiment, reliable multicast provides reliability forinformation multicast. Usually it is done by negative acknowledgementsor repair requests. As one example, SRM (Scalable Reliable Multicast)lets each multicast recipient be responsible for information loss orerror by requesting a repair from the whole multicast group (notnecessarily from the sender) or by initiating a local recovery.

In yet another embodiment, broadcasting and flooding are used to reachmultiple destinations with a best effort in just one sessiontransmission. A recipient may receive more than one copy of exactly thesame information, which inadvertently gives rise to some level ofredundancy by heavy use of bandwidth. The broadcast and flooding methodsassume that all members are following the rules, and that delivery on alink level is assured.

In a further embodiment, a dynamic redundant transmission policy, withMarkov decision theory, is used to find the optimal policy numerically.By relaxing the integer requirement on the number of packetstransmitted, the system explicitly finds a real-time recursion for theoptimal transmission function. The properties of this recursion are thenanalyzed to propose a simple numerical procedure for finding the minimumover all real valued transmission functions, by searching over aone-dimensional parameter space. This then yields an implementable,suboptimal policy when discretized to integer values.

In addition to software, the system uses redundant transceivers andantennas to improve reliability. One embodiment increases node densityin order to reduce required transmitter power and enable shorter linkdistances. A mesh topology allows a device to have multiple next-hopneighbors to communicate with and therefore spatial diversity in termsof multiple transmission paths. Higher node density will also permitshorter distances between devices and can result in increased receivedsignal strength and improved signal-to-noise ratios.

FIG. 1D describes generally, an example of transceiver for receivingdata over the wireless network. One embodiment can use existingtransceivers such as Zigbee, Bluetooth, WiFi, or the like. Thefrequencies for the MBAN network (2360-2400 MHz) can be aeronauticalmobile telemetry (AMT) frequency. In an embodiment, the central stationor base stations may be equipped with the different spatially separatedantennas and switch the antennas in a round-robin fashion such as whilereceiving or transmitting data over the MBAN network. In an embodiment,the antennas described herein may directional antennas that may beemployed on the wireless devices. In an example, Microstrip antennas maybe used by the system that may have a patch area of 3.2×3.2 cm2, whichmay allow the placement of these antennas on front, back, or any othersides of the wireless devices. Unlike digital beamforming, the passivedirectional antennas described herein may produce a directionalradiation pattern without extra circuitry or power. In an embodiment,with a directional radiation pattern pointed at the right direction, awireless client (such as a doctor or a patient) may use reduced transmitpower such as to deliver a required receiver signal strength (RSS), orit may increase the RSS with the same transmit power. Further, theclient's interference to its peers may also be reduced. In anembodiment, the term “antenna” may refer to the passive antenna withoutthe RF chain.

In an embodiment, the multiple directional antennas (such as antenna 1to n) may be placed on the surface of the wireless devices such as toselect one for directional transmission without adding RF circuitry, incontrast to the simultaneous use of multiple RF chains by beamforming.In an embodiment, the antennas and hospital wireless monitoring systemmay allow communication to and from the wireless devices in the MBAN. Inan embodiment, the wireless devices receive communications coversbandwidth of 2360-2400 MHz, 2300-2305 MHz and 2395-2400 MHz, 2400-2483.5MHz, 5150-5250 MHz, and the like. In an embodiment, the system mayinclude one or more transceivers configured to transmit and receivecommunications using different frequency band.

In an embodiment, a challenge for the system is the rotation of thewireless devices during the wireless access. In an embodiment, thedevice orientation may be critical during the use of the directionalantenna because a wireless device can rotate and the rotation may changethe device direction much faster than mobility does. The system may beconfigured to collect accelerometer and compass readings along withnetwork usage information from different wireless devices in the field.From such field-collected traces, the system may be configured toestimate the orientation and rotation of the wireless devices during thewireless usage.

In an embodiment, the orientation and rotation may impact thedirectional channels. In an implementation, the system may uses acomputerized motor platform such as to measure the Received SignalStrength Indicator (RSSI) of directional antennas for indoor andnon-line-of-sight (NLOS) environments, with not only con-trolledorientations, but also rotation according to the field collected traces.In an embodiment, the system may present the directional antennasoutperform omni-directional ones for a considerable range oforientations even in NLOS indoor environments. In an embodiment, thedirectional channels may be highly reciprocal for 802.11 like frequencybands, and their performance may be predictable in short intervals evenunder realistic rotations.

In an embodiment, another challenge is to allow the wireless devices todynamically select the best antenna. The system may use a multi-antennasystem that may consist of an omni directional antenna, one or moredirectional antennas, and an antenna switch. In an embodiment, thesystem works with existing mobile devices that may include a single RFchain and may use only one antenna at a time. In an embodiment, twoantenna selection methods such as a packet-based method and asymbol-based method are disclosed herein. The packet-based method mayuse one packet to assess an antenna without any changes to the networkinfrastructure. The symbol-based method may use the PHY training symbolssuch that all antennas are assessed with a single packet. In anembodiment, the use of antenna selection methods, the directionalantennas may be effectively employed to improve the transmission gain ofwireless devices by almost 3 dB under various propagation environmentsand realistic rotation. Such gain may be achieved without any change tothe deployed network infrastructure such as MBAN.

In another embodiment, antenna redundancy is applied to a centralstation (base station, access point) with a number K of spatiallyseparated antennas, and to switch the antennas in a round-robin fashionwhen performing retransmissions for frames directed from the basestation to a wireless station. As an example, the first packet istransmitted on antenna 1, the first retransmission on antenna 2, thesecond retransmission on antenna 3 and so forth.

Alternatively, a number K of tightly synchronized and coupled basestations can be used to achieve the same effect. The system could alsouse different center frequencies to obtain different channels, but usingmultiple antennas and spatially diverse channels is more advantageous ifobstacles move from time to time in the path between transmission. Thisapproach leverages transmit diversity (and of receiver diversity in thecase of packets sent from the wireless station to the access point)while keeping the complexity of the receiver low, as compared to truetransmit diversity/MIMO systems. This makes antenna redundancyattractive for scenarios where the wireless stations are small and cheapfield devices. For the case of independent (and rather bad) channelsbetween the antennas and a wireless station the antenna redundancyapproach decreases the failure probability (i.e. the probability of arequest to miss its deadline) exponentially in the number of antennas.For the investigated scenario the difference is approximately one orderof magnitude per additional antenna. In addition, already for the secondantenna, the system achieves a significant reduction in the mean numberof packets needed to transmit a request. This saves an enormous amountof bandwidth, which can be used to serve other wireless stations. Whenadditionally the antenna reuse strategy is used, then for scenarios withlow request inter-arrival periods (as often found in hospitalapplications) further bandwidth savings can be achieved. This approachis highly effective with antenna redundancy for cases where the channelsare not independent but correlated, e.g. for the case where the wirelessstation is located close to an interferer (surgical knives). In thesesituations, the best antenna is preferentially used for the cluster oftransmission nodes.

In an embodiment, the MBAN can facilitate data redundancy andretransmission techniques such as to high availability data storage,file replication, and some fault tolerant techniques. The securitymechanisms can have different characteristics that require differentapproaches to redundancy. The MBAN can use redundancy to increaseassurance of security and data delivery. In an embodiment, differenttransmission mechanism can be used such as to wirelessly transfer thedata among the devices of the system.

In an embodiment, the devices may transmit messages among each in theMBAN. However, in the face of interference such as surgical knives, themessage may not be successfully received by the receivers. In anembodiment, the communications may be acknowledged to ensure thereliable delivery of data among the devices. In an embodiment, eachdevice may be configured to include a brief time window in which it isrequired to send back a short message acknowledging the receipt of thedata. In an embodiment, the transmitter or the transmitting device maybe configured to wait for the acknowledgement receipt or responsemessage from the receivers such as to ensure the reliable delivery ofthe data. In an embodiment, if the acknowledgement is received withinbrief time window then the transmitting device or the transmitter mayassume that the message or the data is not received by the receiver andresend the message again. In an embodiment, the process may repeatsuntil the message and acknowledgement are both received. In anembodiment, if even after a few tries the data is not acknowledged bythe receiver then the transmitter may be configured to reports a failurenotification to the system.

In an implementation, the module 77 may use mesh networking to make thewireless links as reliable as possible. In an embodiment, the devices ofinterest may configured to be placed close together to each other suchthat a robust network can be formed such as by simply allowing some ofthem to route messages on each other's behalf. In an embodiment, thebetter use of the channel may be made if devices limit their transmitpower and communicate only with their near neighbours. Once a meshnetwork is in place, a number of possible paths may exist between thedevices in the MBAN network. In an embodiment, the module 77 may exploitthe path diversity such as by using a form of dynamic routingtechniques. In an embodiment, the module 77 may allow the system todetermine a path failure, as a result of interference or some otherchange in the environment, the network may pick a different path for thesystem to transfer the data. In an embodiment, a single-hoptransmissions may acknowledged and retried if they fail, multi-hoptransmissions through the mesh may also be acknowledged and retried.

In an embodiment, a robust rate adaptation scheme that can be resilientto jamming from surgical knives and other interference sources isdisclosed. In an embodiment, the network devices jamming may be detectedsuch as by measuring PDR (Packet Delivery Ratio) with SS (SignalStrength). In an embodiment, the rate adaptation scheme described hereinmay detect jamming from surgical knives or other equipment and selectthe data transmission mode, which may include the expected maximumthroughput. Through the performance evaluations, the rate adaptationscheme may improve the packet delivery ratio and the wireless linkutilization in the MBAN network. In an embodiment, it may also improvethe wireless link utilization by detecting jamming interference andadapting the data transmission mode (modulation and coding levels) tothe successful transmission probability.

In another embodiment, an effective approach to diminish the impact of astatistical jammer on TDMA-based MAC protocols is to eliminate thepossibility to extract patterns in the wireless network (such as MBAN).In an embodiment, the system may be configured to use these patternsappear as a result of the use of fixed schedules, which may be set whenone or more nodes joins the wireless network and may be assumed torepeat till the network is disbanded. In an embodiment, such simple andrepetitive patterns may be maintained with tight time synchronizationand may result in minimal energy consumption, deterministic end-to-enddelay and perhaps maximal transmission concurrency. In an embodiment,the system may be configured to maintain the time synchronization andchange the schedule, transmission duration and routes in a randomizedyet coordinated manner along small time scales such that impact of thejamming may be reduced in the wireless network.

Transfer Control Protocol (TCP) can provide reliable one-to-oneinformation transmission on top of the IP layer, at which an IP packetis routed to the destination devices along a dynamically determinedphysical path. If a TCP packet is lost according to acknowledgementinformation from the receiver, or if its own retransmission timer timesout, a TCP sender retransmits the TCP packet. In an embodiment if thedata packet is blocked by one or more path interruption threats then thepacket can be retransmitted by the system, since the system may get areport that the packet is missing. Further, the system can implementtime out techniques before hearing any acknowledgement such that thesystem can retransmit the data packets if dropping or damaging ofacknowledgement.

In an implementation, reliable multicast technique can providereliability for information multicast. This can be done by negativeacknowledgements or repair requests. For example Scalable ReliableMulticast (SRM) can let each multicast device be responsible forinformation loss or error by requesting a repair from the wholemulticast group (not necessarily from the sender) or by initiating alocal recovery.

In an embodiment, broadcasting and flooding techniques can be used suchas to reach multiple destinations in one session transmission. In MBANnetwork the receiver may receive more than one copy of exactly the sameinformation, which inadvertently gives rise to some level of redundancyof data. The standard broadcast and flooding techniques assume that allreceivers are following the rules, and that delivery on a link level isassured.

In an implementation, high availability data storage techniques can beused that can include one or more one disks to store a copy of the dataor the data is dispersed to more than one disk with built-in redundancysuch as to deal with disk crashes and provide lower latency for dataaccess.

In an implementation, file replication techniques can be used to makereplicas to support easier access to the data among the devices.Establishing mirror web sites for lower latency is one such example. Thedata backup can be done periodically such as to help restore damaged orlost files from backed-up copies.

In hospital wireless monitoring system, replicated execution may beemployed to run a program concurrently at multiple places. Thecomputation can smoothly continue if one execution succeeds. Mapping onetransceiver to several different server machines, in a round robinfashion or other more sophisticated way, can prevent one single serverfrom being overloaded and ensure that the data can be accessible even ifsome server machines have crashed.

In an embodiment, redundancy may be improved by simply increasing thenumber of the sources or database of same information or the number oftransmission paths, particularly when information corruption isdetected.

In an embodiment, the system may suffer from data packet drops,transmitting multiple, redundant packets during each sampling intervalcan improve estimation performance, but at the expense of a highercommunication rate. To avoid this, the system can implement techniquessuch as by relaxing the integer requirement on the number of packetstransmitted and identifying real-time recursion for the optimaltransmission function.

The technique may implement redundant transmission policies for stateestimation of unstable stochastic linear systems over packet droppingchannels such as by relaxing the integer requirement on the number ofpackets transmitted during each sampling interval. The system candetermine a real-time recursion for the optimal transmission function.The system can analyze the properties of this recursion such as topropose a simple numerical procedure for finding the minimum over allreal-valued transmission functions, which may yield an implementablepolicy when discretized.

In an embodiment, the system can implement antenna redundancytechniques, which can use different transmitter antennas for performingthe data retransmissions. The antenna redundancy technique can equip thesystem (such as central station, base station, access point, and thelike) with a number K of spatially separated antennas capable ofswitching the antennas in a round-robin fashion when performingretransmissions for frames directed in the MBAN network. For example,the first packet can be transmitted on antenna 1, the firstretransmission on antenna 2, the second retransmission on antenna 3 andso forth. In an embodiment, different frequencies can be used to obtaindifferent channels. The use of multiple antennas and spatially diversechannels can be advantageous if obstacles move from time to time in thepath between transmitter and receiver, which may happen due to mobility.

In an embodiment, an example of the antenna redundancy technique with Kantennas is disclosed. A packet directed from or to the MBAN network canbe first transmitted over antenna 1. If there is need for aretransmission, then antenna 2 can be used. If another retransmission isneeded, antenna 3 can be used and so forth, until the packet issuccessfully received or a prescribed deadline for transmitting therequest expires. The antennas described herein can be used inround-robin fashion.

FIG. 1E shows another exemplary module with redundant transceivers andredundant antennas. The module includes a plurality of transceivers, forexample transceivers that can be selectively operated between 860 MHz to2.4 GHz, UWB transceiver, and optical transceivers. In this embodiment,the system may employ a simple “listen before you talk” strategy suchthat the device may be configured to listen such as to check if thechannel is busy, and if it is, then the device may wait before checkingagain. In an embodiment, if the channel is busy and the device keeps onfailing to find a clear channel then module 77 can perform exceptionhandling during the jamming period in a number of ways, such as:

-   -   1) perform frequency hopping between major bands such as AMT 2.4        GHz with 16 channels, 915 MHz and 868 MHz. This can be done by        providing programmable/selectable crystals as inputs to the RF        transceiver to periodically alter the frequency. The frequency        hopping can be done at preprogrammed intervals or the mesh        transceivers can tell each other to flock to new frequency if        jamming is detected. In an embodiment, various spreading methods        may be commonly used, but the essential idea behind all of them        may be to use a bandwidth that may be several orders of        magnitude greater than strictly required by the information that        is sent. In an embodiment, the signal may be spread over a large        bandwidth that may coexist with narrow-band signals, which        generally appear to the spread-spectrum receiver as a slight        reduction in the signal-to-noise ratio over the spectrum being        used;    -   2) place directional antenna on patient bed or directly under        patient so that the antenna is very close to transceivers worn        by patient and can wirelessly receive data and transfer data        back to monitoring devices using power-line transceiver        networks;    -   3) place directional antenna on patient bed (or use patient bed        as antenna) so that it is very close to transceivers worn by        patient to wirelessly receive data and have a wired connection        back to monitoring devices to minimize risk of jamming;    -   4) transmit through slower optical transceivers (infrared        transceivers such as those on TV remote controls) to transmit        data during period where the RF transceivers could not transmit        due to jamming;    -   5) use ultrawideband (UWB) transceivers in short duration to        transmit data during period where the transceivers could not        transmit due to jamming.

FIG. 1F shows a multi-band frequency hopping embodiment. In thisembodiment, technique for robust transmission of data in the MBANnetwork is disclosed. The traditional defenses against jamming mayfrequency hopping at the physical layer. In an embodiment, the frequencyhopping technique may be implemented between major bands such as AMT 2.4GHz with 16 channels, 915 MHz and 868 MHz, and the like. In anembodiment, the technique may allow the signal hops from channel tochannel such as by transmitting short bursts of data at each channel fora set period of time. This may be implemented by providing programmableor selectable crystals as inputs to the RF transceiver to periodicallyalter the frequency. This may be done at preprogrammed intervals suchthat the meshed transceivers may inform each other to flock to newfrequency if jamming is detected.

FIG. 1G shows a bed antenna embodiment. In this embodiment, distance mayhave a strong influence on the signal loss or jamming in the MBANnetwork. In an embodiment, the directional antenna may be placed on thepatient bed or directly under the patient such that it may be very closeto the transceivers worn by the patient. In an embodiment, thetransceivers can wirelessly receive data and transfer data back to themonitoring devices (such as devices of the hospital monitoring system)using power line transceiver networks, there by substantially reducingthe risk of jamming in the MBAN network.

FIG. 1H shows a bed receiver with large antenna where the receiver iswired to hospital monitoring equipment. In this embodiment, thedirectional antenna may be placed on the patient bed (or may use patientbed as antenna) such that it may be very close to transceivers worn bythe patient. In an embodiment, the transceivers can wirelessly receivedata and may include a wired connection back to the monitoring devicessuch as to minimize risk of jamming.

FIG. 1I shows a multi-band system that transmits over RF and opticalbands. In this embodiment, one technique by which the system may reduceor avoid the jamming is by using slower optical transceivers. In anembodiment, the slower optical transceivers described herein may includefor example, infrared transceivers such as those on TV remote controls.In an embodiment, the system may be configured to detect the jammingsuch as by determining the RF energy threshold level for an openchannel. For example, if the RF energy threshold level for an open issuch that no data may be transmitted by the transceivers for a longtime, then in an embodiment, slower optical infrared (IR) transceiversmay be configured to transmit the data during such period where thewireless transceivers may not transmit the data due to RF interferenceor jamming. At the end of interference, the system switches back to theregular transceiver for speed and power optimization.

FIG. 1J shows a multi-band system that transmits over ultra-wideban,Zigbee, WiFi and optical bands. In an embodiment, power hungry ultrawideband transceivers may be used to for reliable transfer of data inthe MBAN network. In an embodiment, the system may be configured todetect the jamming such as by determining the RF energy threshold levelfor an open channel. For example, if the RF energy threshold level foran open channel indicates that transmission cannot be done for anextended period (due to interference), where no data may be transmittedby the transceivers, then power hungry ultra wideband transceivers maybe configured to transmit data during the short period where thetransceivers may not transmit due to jamming. At the end ofinterference, the system switches back to the regular transceiver forspeed and power optimization.

FIG. 1K shows mesh networking that transmits over various wireless andoptical protocols in a node to node basis to avoid a jammed node forenhanced reliability. In an implementation, the system may uses meshnetworking technology such as to make the wireless links as reliable aspossible. In one implementation, the use of ultrawideband, Zigbee, WiFi,AMT, and optical transceivers, each of which connected to correspondingmesh network for ultrawideband, Zigbee, WiFi, AMT, and opticaltransceivers, renders the system super reliable for patient telemetry.In an embodiment, the devices of interest may be configured to be placedclose together to each other such that a robust network can be formedsuch as by simply allowing some of them to route messages on eachother's behalf. In an embodiment, the better use of the channel may bemade if devices limit their transmit power and communicate only withtheir near neighbors. In an embodiment, the mesh network may include anumber of possible paths between the devices in the network (such asMBAN). In an embodiment, if the path chosen by the transceivers may isfailed, as a result of interference or some other change in theenvironment, the network may pick a different path for the system totransfer the data. Thus, the system avoids interference or jamming byallowing the mesh transceivers' to immediate switch to another path.

FIG. 1L shows exemplary low power cells for patient telemetry. In anembodiment, the effects of jamming may be reduced such by reducing thetransmission range for each wireless node (cell size) in the network. Inan embodiment, the cell sizes may be as small as possible such as tomake full use of the limited maximum output power of the monitoringdevices and to increase the number of possible call re-establishmentcells. In an embodiment, the small cell size avoids or reduces the riskof jamming such as by handover to another cell for data transmission.

In an embodiment, the resistance to the jamming may be increased byslowing down the data rate of transmissions. In an embodiment, as thedata transmission rate decreases, the signal-to-noise ratio increases,thereby minimizing jamming in the MBAN network.

FIG. 1M shows an embodiment with scheduled transmissions. In anembodiment, the impact of jamming is diminished by using scheduledtransmission techniques. In an embodiment, the system may implementtight time synchronization techniques and may result in minimal energyconsumption, deterministic end-to-end delay and perhaps maximaltransmission concurrency. In an embodiment, the systems maysynchronization signal to be transmitted between the transceivers andthe monitoring devices. In an embodiment, the system may be configuredto maintain the time synchronization and change the schedule periods andtransmission route in randomly on small time periods such that impact ofthe jamming may be reduced in the MBAN.

FIG. 1N shows an exemplary high gain parabolic bed antenna. In thisembodiment, the parabolic antenna is positioned under the patient andthe focus of the antenna is aimed at the RF transceiver on a wearableappliance mounted on the patient. The parabolic antenna captures signalsfrom the RF transceiver or signals that bounce off objects such as wallor furniture, for example. The radiation pattern of the feed antenna hasto be tailored to the shape of the dish, because it has a stronginfluence on the aperture efficiency, which determines the antenna gain.Radiation from the feed that falls outside the edge of the dish iscalled “spillover” and is wasted, reducing the gain and increasing thebacklobes, possibly causing interference or (in receiving antennas)increasing susceptibility to ground noise. However, maximum gain is onlyachieved when the dish is uniformly “illuminated” with a constant fieldstrength to its edges. So the ideal radiation pattern of a feed antennawould be a constant field strength throughout the solid angle of thedish, dropping abruptly to zero at the edges.

In one embodiment, a technique called “dual reflector shaping” may beused. This involves changing the shape of the sub-reflector (usually ina Cassegrain configuration) to map the known pattern of the feed into auniform illumination of the primary, to maximize the gain. However, thisresults in a secondary that is no longer precisely hyperbolic (though itis still very close), so the constant phase property is lost. This phaseerror, however, can be compensated for by slightly tweaking the shape ofthe primary mirror. The result is a higher gain, or gain/spilloverratio.

Parabolic antennas can use the following type of feed, that is, how theradio waves are supplied to the antenna. One embodiment is an axial orfront feed—This is the most common type of feed, with the feed antennalocated in front of the dish at the focus, on the beam axis. Adisadvantage of this type is that the feed and its supports block someof the beam, which limits the aperture efficiency. Another embodiment isan off-axis or offset feed—The reflector is an asymmetrical segment of aparaboloid, so the focus, and the feed antenna, are located to one sideof the dish. The purpose of this design is to move the feed structureout of the beam path, so it doesn't block the beam. Offset feed is alsoused in multiple reflector designs such as the Cassegrain and Gregorian.In a Cassegrain embodiment, the Cassegrain antenna the feed is locatedon or behind the dish, and radiates forward, illuminating a convexhyperboloidal secondary reflector at the focus of the dish. The radiowaves from the feed reflect back off the secondary reflector to thedish, which forms the outgoing beam. An advantage of this configurationis that the feed, with its waveguides and “front end” electronics doesnot have to be suspended in front of the dish, so it is used forantennas with complicated or bulky feeds, such as large satellitecommunication antennas and radio telescopes. In another embodiment, aGregorian design is used which is similar to the Cassegrain designexcept that the secondary reflector is concave, (ellipsoidal) in shape.Aperture efficiency over 70% can be achieved.

Advantages of the wireless monitoring system can include one or more ofthe following. Patients will enjoy greater mobility when wires can bedispensed with Immobilized patients are at higher risk for emboli,wasting, bed sores, pneumonias, and other problems. Since cables must besterilized after use by one patient and before use by another, awireless approach may decrease the risk of cross-infection. The systempresents opportunities for cost savings as well. Earlier intervention isoften cheaper, more effective intervention. Wireless monitoring requiresfewer staff than more conventional approaches. Sometimes, patients areadmitted to ICUs not so much for specialized nursing care as becausethey need monitoring. If the same monitoring could be carried out inless costly settings, the savings could be appreciable. While aspresently envisioned wireless monitoring is intended for hospital use,these devices could also help protect soldiers in combat, and eventuallythe technology may become suitable for home use. The system can be usedfor remotely monitoring critically and chronically ill people via smallwireless devices so that medical workers can track the person's healthstatus as well as take swift action in emergencies.

By using the system, doctors and nurses in hospitals can avoid having todisconnect patients multiple times, whether it's in an ambulance orvarious areas of a hospital. The system can also speed up diagnoses,reduce readmissions and allow patients to remain in their homes.

In one embodiment, cameras with 3D detection are used to monitor thepatient's ambulation. In the 3D detection process, by putting 3 or moreknown coordinate objects in a scene, camera origin, view direction andup vector can be calculated and the 3D space that each camera views canbe defined.

In one embodiment with two or more cameras, camera parameters (e.g.field of view) are preset to fixed numbers. Each pixel from each cameramaps to a cone space. The system identifies one or more 3D featurepoints (such as a birthmark or an identifiable body landmark) on thepatient. The 3D feature point can be detected by identifying the samepoint from two or more different angles. By determining the intersectionfor the two or more cones, the system determines the position of thefeature point. The above process can be extended to certain featurecurves and surfaces, e.g. straight lines, arcs; flat surfaces,cylindrical surfaces. Thus, the system can detect curves if a featurecurve is known as a straight line or arc. Additionally, the system candetect surfaces if a feature surface is known as a flat or cylindricalsurface. The further the patient is from the camera, the lower theaccuracy of the feature point determination. Also, the presence of morecameras would lead to more correlation data for increased accuracy infeature point determination. When correlated feature points, curves andsurfaces are detected, the remaining surfaces are detected by texturematching and shading changes. Predetermined constraints are appliedbased on silhouette curves from different views. A different constraintcan be applied when one part of the patient is occluded by anotherobject. Further, as the system knows what basic organic shape it isdetecting, the basic profile can be applied and adjusted in the process.

In a single camera embodiment, the 3D feature point (e.g. a birth mark)can be detected if the system can identify the same point from twoframes. The relative motion from the two frames should be small butdetectable. Other features curves and surfaces will be detectedcorrespondingly, but can be tessellated or sampled to generate morefeature points. A transformation matrix is calculated between a set offeature points from the first frame to a set of feature points from thesecond frame. When correlated feature points, curves and surfaces aredetected, the rest of the surfaces will be detected by texture matchingand shading changes.

Each camera exists in a sphere coordinate system where the sphere origin(0,0,0) is defined as the position of the camera. The system detectstheta and phi for each observed object, but not the radius or size ofthe object. The radius is approximated by detecting the size of knownobjects and scaling the size of known objects to the object whose sizeis to be determined. For example, to detect the position of a ball thatis 10 cm in radius, the system detects the ball and scales otherfeatures based on the known ball size. For human, features that areknown in advance include head size and leg length, among others. Surfacetexture can also be detected, but the light and shade information fromdifferent camera views is removed. In either single or multiple cameraembodiments, depending on frame rate and picture resolution, certainundetected areas such as holes can exist. For example, if the patientyawns, the patient's mouth can appear as a hole in an image. For 3Dmodeling purposes, the hole can be filled by blending neighborhoodsurfaces. The blended surfaces are behind the visible line.

In one embodiment shown in FIG. 2A, each camera is calibrated before 3Ddetection is done. Pseudo-code for one implementation of a cameracalibration process is as follows:

-   -   Place a calibration sheet with known dots at a known distance        (e.g. 1 meter), and perpendicular to a camera view.    -   Take snap shot of the sheet, and correlate the position of the        dots to the camera image:        -   Dot1(x,y,1)←>pixel (x,y)    -   Place a different calibration sheet that contains known dots at        another different known distance (e.g. 2 meters), and        perpendicular to camera view.    -   Take another snapshot of the sheet, and correlate the position        of the dots to the camera image:        -   Dot2(x,y,2)←>pixel (x,y)    -   Smooth the dots and pixels to minimize digitization errors. By        smoothing the map using a global map function, step errors will        be eliminated and each pixel will be mapped to a cone space.    -   For each pixel, draw a line from Dot1(x,y,z) to Dot2(x, y, z)        defining a cone center where the camera can view.    -   One smoothing method is to apply a weighted filter for Dot1 and        Dot2. A weight filter can be used. In one example, the following        exemplary filter is applied.

1 2 1 2 4 2 1 2 1

-   -   Assuming Dot1_Left refers to the value of the dot on the left        side of Dot1 and Dot1_Right refers to the value of the dot to        the right of Dot1 and Dot1_Upper refers to the dot above Dot1,        for example, the resulting smoothed Dot1 value is as follows:        1/16*(Dot1*4+Dot1_Left*2+Dot1_Right*2+Dot1_Upper*2+Dot1_Down*2+Dot1_UpperLeft+Dot1_UpperRight+Dot1_LowerLeft+Dot1_LowerRight)        -   Similarly, the resulting smoothed Dot2 value is as follows:            1/16*(Dot2*4+Dot2_Left*2+Dot2_Right*2+Dot2_Upper*2+Dot2_Down*2+Dot2_UpperLeft+Dot2_UpperRight+Dot2_LowerLeft+Dot2_LowerRight)

In another smoothing method, features from Dot1 sheet are mapped to asub pixel level and features of Dot2 sheet are mapped to a sub pixellevel and smooth them. To illustrate, Dot1 dot center (5, 5, 1) aremapped to pixel (1.05, 2.86), and Dot2 dot center (10, 10, 2) are mappedto pixel (1.15, 2.76). A predetermined correlation function is thenapplied.

FIG. 2B shows an exemplary calibration sheet having a plurality of dots.In this embodiment, the dots can be circular dots and square dots whichare interleaved among each others. The dots should be placed relativelyclose to each other and each dot size should not be too large, so we canhave as many dots as possible in one snapshot. However, the dots shouldnot be placed too close to each other and the dot size should not be toosmall, so they are not identifiable.

A module 54 monitors patient activity and generates a warning if thepatient has fallen. In one implementation, the system detects the speedof center of mass movement. If the center of mass movement is zero for apredetermined period, the patient is either sleeping or unconscious. Thesystem then attempts to signal the patient and receive confirmatorysignals indicating that the patient is conscious. If patient does notconfirm, then the system generates an alarm. For example, if the patienthas fallen, the system would generate an alarm signal that can be sentto friends, relatives or neighbors of the patient. Alternatively, athird party such as a call center can monitor the alarm signal. Besidesmonitoring for falls, the system performs video analysis of the patient.For example, during a particular day, the system can determine theamount of time for exercise, sleep, and entertainment, among others. Thenetwork of sensors in a patient's home can recognize ordinarypatterns—such as eating, sleeping, and greeting visitors—and to alertcaretakers to out-of-the-ordinary ones—such as prolonged inactivity orabsence. For instance, if the patient goes into the bathroom thendisappears off the sensor for 13 minutes and don't show up anywhere elsein the house, the system infers that patient had taken a bath or ashower. However, if a person falls and remains motionless for apredetermined period, the system would record the event and notify adesignated person to get assistance.

A fall detection process (shown in FIG. 3) performs the followingoperations:

-   -   Find floor space area    -   Define camera view background 3D scene    -   Calculate patient's key features    -   Detect fall

In one implementation, pseudo-code for determining the floor space areais as follows:

-   -   2. Sample the camera view space by M by N, e.g. M=1000, N=500.    -   3. Calculate all sample points the 3D coordinates in room        coordinate system; where Z axis is pointing up. Refer to the 3D        detection for how to calculate 3D positions.    -   4. Find the lowest Z value point (Zmin)    -   5. Find all points whose Z values are less than Zmin+Ztol; where        Ztol is a user adjustable value, e.g. 2 inches.    -   6. If rooms have different elevation levels, then excluding the        lowest Z floor points, repeat step 2, 3 and 4 while keeping the        lowest Z is within Ztol2 of previous Z. In this example Ztol2=2        feet, which means the floor level difference should be within 2        feet.    -   7. Detect stairs by finding approximate same flat area but        within equal Z differences between them.    -   8. Optionally, additional information from the user can be used        to define floor space more accurately, especially in single        camera system where the coordinates are less accurate, e.g.:        -   a. Import the CAD file from constructors' blue prints.        -   b. Pick regions from the camera space to define the floor,            then use software to calculate its room coordinates.        -   c. User software to find all flat surfaces, e.g. floors,            counter tops, then user pick the ones, which are actually            floors and/or stairs.

In the implementation, pseudo-code for determining the camera viewbackground 3D scene is as follows:

-   -   1. With the same sample points, calculate x, y coordinates and        the Z depth and calculate 3D positions.    -   2. Determine background scene using one the following methods,        among others:        -   a. When there is nobody in the room.        -   b. Retrieve and update the previous calculated background            scene.        -   c. Continuous updating every sample point when the furthest            Z value was found, that is the background value.

In the implementation, pseudo-code for determining key features of thepatient is as follows:

-   -   1. Foreground objects can be extracted by comparing each sample        point's Z value to the background scene point's Z value, if it        is smaller, then it is on the foreground.    -   2. In normal condition, the feet/shoe can be detected by finding        the lowest Z point clouds close the floor in room space, its        color will be extracted.    -   3. In normal condition, the hair/hat can be detected by finding        the highest Z point clouds close the floor in room space, its        color will be extracted.    -   4. The rest of the features can be determined by searching from        either head or toe. E.g, hat, hair, face, eye, mouth, ear,        earring, neck, lipstick, moustache, jacket, limbs, belt, ring,        hand, etc.    -   5. The key dimension of features will be determined by        retrieving the historic stored data or recalculated, e.g., head        size, mouth width, arm length, leg length, waist, etc.    -   6. In abnormal conditions, features can be detected by detect        individual features then correlated them to different body        parts. E.g, if patient's skin is black, we can hardly get a        yellow or white face, by detecting eye and nose, we know which        part is the face, then we can detect other characteristics.

To detect fall, the pseudo-code for the embodiment is as follows:

-   -   1. The fall has to be detected in almost real time by tracking        movements of key features very quickly. E.g. if patient has        black hair/face, track the center of the black blob will know        roughly where his head move to.    -   2. Then the center of mass will be tracked, center of mass is        usually around belly button area, so the belt or borderline        between upper and lower body closed will be good indications.    -   3. Patient's fall always coupled with rapid deceleration of        center of mass. Software can adjust this threshold based on        patient age, height and physical conditions.    -   4. Then if the fall is accidental and patient has difficult to        get up, one or more of following will happen:        -   a. Patient will move very slowly to find support object to            get up.        -   b. Patient will wave hand to camera ask for help. To detect            this condition, the patient hand has to be detected first by            finding a blob of points with his skin color. Hand motion            can be tracked by calculate the motion of the center of the            points, if it swings left and right, it means patient is            waving to camera.        -   c. Patient is unconscious, motionless. To detect this            condition, extract the foreground object, calculate its            motion vectors, if it is within certain tolerance, it means            patient is not moving. In the mean time, test how long it            last, if it past a user defined time threshold, it means            patient is in great danger.

In one embodiment for fall detection, the system determines a patientfall-down as when the patient's knee, butt or hand is on the floor. Thefall action is defined a quick deceleration of center of mass, which isaround belly button area. An accidental fall action is defined when thepatient falls down with limited movement for a predetermined period.

The system monitors the patients' fall relative to a floor. In oneembodiment, the plan of the floor is specified in advance by thepatient. Alternatively, the system can automatically determine the floorlayout by examining the movement of the patient's feet and estimated thesurfaces touched by the feet as the floor.

In one embodiment with in door positioning, the user can create afacsimile of the floor plan during initialization by walking around theperimeter of each room and recording his/her movement through thein-door positioning system and when complete, press a button to indicateto the system the type of room such as living room, bed room, bath room,among others. Also, the user can calibrate the floor level by sittingdown and then standing up (or vice versa) and allowing the accelerometerto sense the floor through the user motion. Periodically, the user canrecalibrate the floor plan and/or the floor level.

The system detects a patient fall by detecting a center of mass of anexemplary feature. Thus, the software can monitor the center of one ormore objects, for example the head and toe, the patient's belt, thebottom line of the shirt, or the top line of the pants.

The detection of the fall can be adjusted based on two thresholds:

-   -   a. Speed of deceleration of the center of mass.    -   b. The amount of time that the patient lies motionless on the        floor after the fall.

In one example, once a stroke occurs, the system detects a slow motionof patient as the patient rests or a quick motion as the patientcollapses. By adjust the sensitivity threshold, the system detectswhether a patient is uncomfortable and ready to rest or collapse.

If the center of mass movement ceases to move for a predeterminedperiod, the system can generate the warning. In another embodiment,before generating the warning, the system can request the patient toconfirm that he or she does not need assistance. The confirmation can bein the form of a button that the user can press to override the warning.Alternatively, the confirmation can be in the form of a single utterancethat is then detected by a speech recognizer.

In another embodiment, the confirmatory signal is a patient gesture. Thepatient can nod his or her head to request help and can shake the headto cancel the help request. Alternatively, the patient can use aplurality of hand gestures to signal to the server 20 the actions thatthe patient desires.

By adding other detecting mechanism such as sweat detection, the systemcan know whether patient is uncomfortable or not. Other items that canbe monitored include chest movement (frequency and amplitude) and restlength when the patient sits still in one area, among others.

Besides monitoring for falls, the system performs video analysis of thepatient. For example, during a particular day, the system can determinethe amount of time for exercise, sleep, entertainment, among others. Thenetwork of sensors in a patient's home can recognize ordinarypatterns—such as eating, sleeping, and greeting visitors—and to alertcaretakers to out-of-the-ordinary ones—such as prolonged inactivity orabsence. For instance, if the patient goes into the bathroom thendisappears off the camera 10 view for a predetermined period and doesnot show up anywhere else in the house, the system infers that patienthad taken a bath or a shower. However, if a person falls and remainsmotionless for a predetermined period, the system would record the eventand notify a designated person to get assistance.

In one embodiment, changes in the patient's skin color can be detectedby measuring the current light environment, properly calibrating colorspace between two photos, and then determining global color changebetween two states. Thus, when the patient's face turn red, based on theredness, a severity level warning is generated.

In another embodiment, changes in the patient's face are detected byanalyzing a texture distortion in the images. If the patient perspiresheavily, the texture will show small glisters, make-up smudges, orsweat/tear drippings. Another example is, when long stretched face willbe detected as texture distortion. Agony will show certain wrinkletexture patterns, among others.

The system can also utilize high light changes. Thus, when the patientsweats or changes facial appearance, different high light areas areshown, glisters reflect light and pop up geometry generates more highlight areas.

A module 62 analyzes facial changes such as facial asymmetries. Thechange will be detected by superimpose a newly acquired 3D anatomystructure to a historical (normal) 3D anatomy structure to detectface/eye sagging or excess stretch of facial muscles.

In one embodiment, the system determines a set of base 3D shapes, whichare a set of shapes which can represent extremes of certain facialeffects, e.g. frown, open mouth, smiling, among others. The rest of the3D face shape can be generated by blending/interpolating these baseshapes by applied different weight to each base shapes.

The base 3D shape can be captured using 1) a 3D camera such as camerasfrom Steinbichler, Genex Technology, Minolta 3D, Olympus 3D or 2) one ormore 2D camera with preset camera field of view (FOV) parameters. Tomake it more accurate, one or more special markers can be placed onpatient's face. For example, a known dimension square stick can beplaced on the forehead for camera calibration purposes.

Using the above 3D detection method, facial shapes are then extracted.The proper features (e.g. a wrinkle) will be detected and attached toeach base shape. These features can be animated or blended by changingthe weight of different shape(s). The proper features change can bedetected and determine what type of facial shape it will be.

Next, the system super-imposes two 3D facial shapes (historical ornormal facial shapes and current facial shapes). By matching featuresand geometry of changing areas on the face, closely blended shapes canbe matched and facial shape change detection can be performed. Byoverlaying the two shapes, the abnormal facial change such as saggingeyes or mouth can be detected.

The above processes are used to determine paralysis of specific regionsof the face or disorders in the peripheral or central nervous system(trigeminal paralysis; CVA, among others). The software also detectseyelid positions for evidence of ptosis (incomplete opening of one orboth eyelids) as a sign of innervation problems (CVA; Horner syndrome,for example). The software also checks eye movements for pathologicalconditions, mainly of neurological origin are reflected in aberrationsin eye movement. Pupil reaction is also checked for abnormal reaction ofthe pupil to light (pupil gets smaller the stronger the light) mayindicate various pathological conditions mainly of the nervous system.In patients treated for glaucoma pupillary status and motion pattern maybe important to the follow-up of adequate treatment. The software alsochecks for asymmetry in tongue movement, which is usually indicative ofneurological problems. Another check is neck veins: Engorgement of theneck veins may be an indication of heart failure or obstruction ofnormal blood flow from the head and upper extremities to the heart. Thesoftware also analyzes the face, which is usually a mirror of theemotional state of the observed subject. Fear, joy, anger, apathy areonly some of the emotions that can be readily detected, facialexpressions of emotions are relatively uniform regardless of age, sex,race, etc. This relative uniformity allows for the creation of computerprograms attempting to automatically diagnose people's emotional states.

Speech recognition is performed to determine a change in the form ofspeech (slurred speech, difficulties in the formation of words, forexample) may indicated neurological problems, such an observation canalso indicate some outward effects of various drugs or toxic agents.

In one embodiment shown in FIG. 4, a facial expression analysis processperforms the following operations:

-   -   Find floor space area    -   Define camera view background 3D scene    -   Calculate patient's key features    -   Extract facial objects    -   Detect facial orientation    -   Detect facial expression

The first three steps are already discussed above. The patient's keyfeatures provide information on the location of the face, and once theface area has been determined, other features can be detected bydetecting relative position to each other and special characteristics ofthe features:

-   -   Eye: pupil can be detected by applying Chamfer matching        algorithm, by using stock pupil objects.    -   Hair: located on the top of the head, using previous stored hair        color to locate the hair point clouds.    -   Birthmarks, wrinkles and tattoos: pre store all these features        then use Chamfer matching to locate them.    -   Nose: nose bridge and nose holes usually show special        characteristics for detection, sometime depend on the view        angle, is side view, special silhouette will be shown.    -   Eye browse, Lips and Moustache: All these features have special        colors, e.g. red lipstick; and base shape, e.g. patient has no        expression with mouth closed. Software will locate these        features by color matching, then try to deform the base shape        based on expression, and match shape with expression, we can        detect objects and expression at the same time.    -   Teeth, earring, necklace: All these features can be detected by        color and style, which will give extra information.

In one implementation, pseudo-code for detecting facial orientation isas follows:

-   -   Detect forehead area    -   Use the previously determined features and superimpose them on        the base face model to detect a patient face orientation.

Depends on where patient is facing, for a side facing view, silhouetteedges will provide unique view information because there is a one to onecorrespondent between the view and silhouette shape.

Once the patient's face has been aligned to the right view, exemplarypseudo code to detect facial expression is as follows:

-   -   1. Detect shape change. The shape can be match by superimpose        different expression shapes to current shape, and judge by        minimum discrepancy. E.g. wide mouth open.    -   2. Detect occlusion. Sometime the expression can be detected by        occlusal of another objects, e.g., teeth show up means mouth is        open.    -   3. Detect texture map change. The expression can relate to        certain texture changes, if patient smile, certain wrinkles        patents will show up.    -   4. Detect highlight change. The expression can relate to certain        high light changes, if patient sweats or cries, different        highlight area will show up.

Speech recognition can be performed in one embodiment to determine achange in the form of speech (slurred speech, difficulties in theformation of words, for example) may indicated neurological problems,such an observation can also indicate some outward effects of variousdrugs or toxic agents.

A module communicates with a third party such as the police department,a security monitoring center, or a call center. The module operates witha POTS telephone and can use a broadband medium such as DSL or cablenetwork if available. The module 80 requires that at least the telephoneis available as a lifeline support. In this embodiment, duplex soundtransmission is done using the POTS telephone network. The broadbandnetwork, if available, is optional for high resolution video and otheradvanced services transmission.

During operation, the module checks whether broadband network isavailable. If broadband network is available, the module 80 allows highresolution video, among others, to be broadcasted directly from theserver 20 to the third party or indirectly from the server 20 to theremote server 200 to the third party. In parallel, the module 80 allowssound to be transmitted using the telephone circuit. In this manner,high resolution video can be transmitted since sound data is separatelysent through the POTS network.

If broadband network is not available, the system relies on the POTStelephone network for transmission of voice and images. In this system,one or more images are compressed for burst transmission, and at therequest of the third party or the remote server 200, the telephone'ssound system is placed on hold for a brief period to allow transmissionof images over the POTS network. In this manner, existing POTS lifelinetelephone can be used to monitor patients. The resolution and quantityof images are selectable by the third party. Thus, using only thelifeline as a communication medium, the person monitoring the patientcan elect to only listen, to view one high resolution image with duplextelephone voice transmission, to view a few low resolution images, toview a compressed stream of low resolution video with digitized voice,among others.

During installation or while no live person in the scene, each camerawill capture its own environment objects and store it as backgroundimages, the software then detect the live person in the scene, changesof the live person, so only the portion of live person will be send tothe local server, other compression techniques will be applied, e.g.send changing file, balanced video streaming based on change.

The local server will control and schedule how the video/picture will besend, e.g. when the camera is view an empty room, no pictures will besent, the local server will also determine which camera is at the rightview, and request only the corresponding video be sent. The local serverwill determine which feature it is interested in looking at, e.g. faceand request only that portion be sent.

With predetermined background images and local server controlledstreaming, the system will enable higher resolution and more camerasystem by using narrower bandwidth.

Through this module, a police officer, a security agent, or a healthcareagent such as a physician at a remote location can engage, ininteractive visual communication with the patient. The patient's healthdata or audio-visual signal can be remotely accessed. The patient alsohas access to a video transmission of the third party. Should thepatient experience health symptoms requiring intervention and immediatecare, the health care practitioner at the central station may summonhelp from an emergency services provider. The emergency servicesprovider may send an ambulance, fire department personnel, familymember, or other emergency personnel to the patient's remote location.The emergency services provider may, perhaps, be an ambulance facility,a police station, the local fire department, or any suitable supportfacility.

Communication between the patient's remote location and the centralstation can be initiated by a variety of techniques. One method is bymanually or automatically placing a call on the telephone to thepatient's home or from the patient's home to the central station.

Alternatively, the system can ask a confirmatory question to the patientthrough text to speech software. The patient can be orally instructed bythe health practitioner to conduct specific physical activities such asspecific arm movements, walking, bending, among others. The examinationbegins during the initial conversation with the monitored subject. Anychanges in the spontaneous gestures of the body, arms and hands duringspeech as well as the fulfillment of nonspecific tasks are importantsigns of possible pathological events. The monitoring person caninstruct the monitored subject to perform a series of simple tasks whichcan be used for diagnosis of neurological abnormalities. Theseobservations may yield early indicators of the onset of a disease.

A network 100 such as the Internet receives images from the server 20and passes the data to one or more remote servers 200. The images aretransmitted from the server 200 over a secure communication link such asvirtual private network (VPN) to the remote server(s) 200.

In one embodiment where cameras are deployed, the server 200 collectsdata from a plurality of cameras and uses the 3D images technology todetermine if the patient needs help. The system can transmit video (liveor archived) to the friend, relative, neighbor, or call center for humanreview. At each viewer site, after a viewer specifies the correct URL tothe client browser computer, a connection with the server 200 isestablished and user identity authenticated using suitable password orother security mechanisms. The server 200 then retrieves the documentfrom its local disk or cache memory storage and transmits the contentover the network. In the typical scenario, the user of a Web browserrequests that a media stream file be downloaded, such as sending, inparticular, the URL of a media redirection file from a Web server. Themedia redirection file (MRF) is a type of specialized Hypertext MarkupLanguage (HTML) file that contains instructions for how to locate themultimedia file and in what format the multimedia file is in. The Webserver returns the MRF file to the user's browser program. The browserprogram then reads the MRF file to determine the location of the mediaserver containing one or more multimedia content files. The browser thenlaunches the associated media player application program and passes theMRF file to it. The media player reads the MRF file to obtain theinformation needed to open a connection to a media server, such as aURL, and the required protocol information, depending upon the type ofmedial content is in the file. The streaming media content file is thenrouted from the media server down to the user.

In the camera embodiment, the transactions between the server 200 andone of the remote servers 200 are detailed. The server 200 compares oneimage frame to the next image frame. If no difference exists, theduplicate frame is deleted to minimize storage space. If a differenceexists, only the difference information is stored as described in theJPEG standard. This operation effectively compresses video informationso that the camera images can be transmitted even at telephone modemspeed of 64 k or less. More aggressive compression techniques can beused. For example, patient movements can be clusterized into a group ofknown motion vectors, and patient movements can be described using a setof vectors. Only the vector data is saved. During view back, each vectoris translated into a picture object which is suitably rasterized. Theinformation can also be compressed as motion information.

Next, the server 200 transmits the compressed video to the remote server200. The server 200 stores and caches the video data so that multipleviewers can view the images at once since the server 200 is connected toa network link such as telephone line modem, cable modem, DSL modem, andATM transceiver, among others.

In one implementation, the servers 200 use RAID-5 striping and paritytechniques to organize data in a fault tolerant and efficient manner.The RAID (Redundant Array of Inexpensive Disks) approach is welldescribed in the literature and has various levels of operation,including RAID-5, and the data organization can achieve data storage ina fault tolerant and load balanced manner. RAID-5 provides that thestored data is spread among three or more disk drives, in a redundantmanner, so that even if one of the disk drives fails, the data stored onthe drive can be recovered in an efficient and error free manner fromthe other storage locations. This method also advantageously makes useof each of the disk drives in relatively equal and substantiallyparallel operations. Accordingly, if one has a six gigabyte clustervolume which spans three disk drives, each disk drive would beresponsible for servicing two gigabytes of the cluster volume. Each twogigabyte drive would be comprised of one-third redundant information, toprovide the redundant, and thus fault tolerant, operation required forthe RAID-5 approach. For additional physical security, the server can bestored in a Fire Safe or other secured box, so there is no chance toerase the recorded data, this is very important for forensic analysis.

The system can also monitor the patient's gait pattern and generatewarnings should the patient's gait patterns indicate that the patient islikely to fall. The system will detect patient skeleton structure,stride and frequency; and based on this information to judge whetherpatient has joint problem, asymmetrical bone structure, among others.The system can store historical gait information, and by overlayingcurrent structure to the historical (normal) gait information, gaitchanges can be detected. In the camera embodiment, an estimate of thegait pattern is done using the camera. In a camera-less embodiment, thegait can be sensed by providing a sensor on the floor and a sensor nearthe head and the variance in the two sensor positions are used toestimate gait characteristics.

The system also provides a patient interface 90 to assist the patient ineasily accessing information. In one embodiment, the patient interfaceincludes a touch screen; voice-activated text reading; one touchtelephone dialing; and video conferencing. The touch screen has largeicons that are pre-selected to the patient's needs, such as his or herfavorite web sites or application programs. The voice activated textreading allows a user with poor eye-sight to get information from thepatient interface 90. Buttons with pre-designated dialing numbers, orvideo conferencing contact information allow the user to call a friendor a healthcare provider quickly.

In one embodiment, medicine for the patient is tracked using radiofrequency identification (RFID) tags. In this embodiment, each drugcontainer is tracked through an RFID tag that is also a drug label. TheRF tag is an integrated circuit that is coupled with a mini-antenna totransmit data. The circuit contains memory that stores theidentification Code and other pertinent data to be transmitted when thechip is activated or interrogated using radio energy from a reader. Areader consists of an RF antenna, transceiver and a micro-processor. Thetransceiver sends activation signals to and receives identification datafrom the tag. The antenna may be enclosed with the reader or locatedoutside the reader as a separate piece. RFID readers communicatedirectly with the RFID tags and send encrypted usage data over thepatient's network to the server 200 and eventually over the Internet100. The readers can be built directly into the walls or the cabinetdoors.

In one embodiment, capacitively coupled RFID tags are used. Thecapacitive RFID tag includes a silicon microprocessor that can store 96bits of information, including the pharmaceutical manufacturer, drugname, usage instruction and a 40-bit serial number. A conductive carbonink acts as the tag's antenna and is applied to a paper substratethrough conventional printing means. The silicon chip is attached toprinted carbon-ink electrodes on the back of a paper label, creating alow-cost, disposable tag that can be integrated on the drug label. Theinformation stored on the drug labels is written in a Medicine MarkupLanguage (MML), which is based on the eXtensible Markup Language (XML).MML would allow all computers to communicate with any computer system ina similar way that Web servers read Hyper Text Markup Language (HTML),the common language used to create Web pages.

After receiving the medicine container, the patient places the medicinein a medicine cabinet, which is also equipped with a tag reader. Thissmart cabinet then tracks all medicine stored in it. It can track themedicine taken, how often the medicine is restocked and can let thepatient know when a particular medication is about to expire. At thispoint, the server 200 can order these items automatically. The server200 also monitors drug compliance, and if the patient does not removethe bottle to dispense medication as prescribed, the server 200 sends awarning to the healthcare provider.

The user's habits can be determined by the system. This is done bytracking location, ambulatory travel vectors and time in a database.Thus, if the user typically sleeps between 10 pm to 6 am, the locationwould reflect that the user's location maps to the bedroom between 10 pmand 6 am. In one exemplary system, the system builds a schedule of theuser's activity as follows:

Location Time Start Time End Heart Rate Bed room 10 pm 6 am 60-80 Gymroom 6 am 7 am 90-120 Bath room 7 am 7:30 am 85-120 Dining room 7:30 am8:45 am 80-90 Home Office 8:45 am 11:30 am 85-100 . . . . . .

The habit tracking is adaptive in that it gradually adjusts to theuser's new habits. If there are sudden changes, the system flags thesesudden changes for follow up. For instance, if the user spends threehours in the bathroom, the system prompts the third party (such as acall center) to follow up with the patient to make sure he or she doesnot need help.

In one embodiment, data driven analyzers may be used to track thepatient's habits. These data driven analyzers may incorporate a numberof models such as parametric statistical models, non-parametricstatistical models, clustering models, nearest neighbor models,regression methods, and engineered (artificial) neural networks. Priorto operation, data driven analyzers or models of the patient's habits orambulation patterns are built using one or more training sessions. Thedata used to build the analyzer or model in these sessions are typicallyreferred to as training data. As data driven analyzers are developed byexamining only training examples, the selection of the training data cansignificantly affect the accuracy and the learning speed of the datadriven analyzer. One approach used heretofore generates a separate dataset referred to as a test set for training purposes. The test set isused to avoid overfitting the model or analyzer to the training data.Overfitting refers to the situation where the analyzer has memorized thetraining data so well that it fails to fit or categorize unseen data.Typically, during the construction of the analyzer or model, theanalyzer's performance is tested against the test set. The selection ofthe analyzer or model parameters is performed iteratively until theperformance of the analyzer in classifying the test set reaches anoptimal point. At this point, the training process is completed. Analternative to using an independent training and test set is to use amethodology called cross-validation. Cross-validation can be used todetermine parameter values for a parametric analyzer or model for anon-parametric analyzer. In cross-validation, a single training data setis selected. Next, a number of different analyzers or models are builtby presenting different parts of the training data as test sets to theanalyzers in an iterative process. The parameter or model structure isthen determined on the basis of the combined performance of all modelsor analyzers. Under the cross-validation approach, the analyzer or modelis typically retrained with data using the determined optimal modelstructure.

In one embodiment, clustering operations are performed to detectpatterns in the data. In another embodiment, a neural network is used torecognize each pattern as the neural network is quite robust atrecognizing user habits or patterns. Once the treatment features havebeen characterized, the neural network then compares the input userinformation with stored templates of treatment vocabulary known by theneural network recognizer, among others. The recognition models caninclude a Hidden Markov Model (HMM), a dynamic programming model, aneural network, a fuzzy logic, or a template matcher, among others.These models may be used singly or in combination.

Dynamic programming considers all possible points within the permitteddomain for each value of i. Because the best path from the current pointto the next point is independent of what happens beyond that point.Thus, the total cost of [i(k), j(k)] is the cost of the point itselfplus the cost of the minimum path to it. Preferably, the values of thepredecessors can be kept in an M×N array, and the accumulated cost keptin a 2×N array to contain the accumulated costs of the immediatelypreceding column and the current column. However, this method requiressignificant computing resources. For the recognizer to find the optimaltime alignment between a sequence of frames and a sequence of nodemodels, it must compare most frames against a plurality of node models.One method of reducing the amount of computation required for dynamicprogramming is to use pruning Pruning terminates the dynamic programmingof a given portion of user habit information against a given treatmentmodel if the partial probability score for that comparison drops below agiven threshold. This greatly reduces computation.

Considered to be a generalization of dynamic programming, a hiddenMarkov model is used in the preferred embodiment to evaluate theprobability of occurrence of a sequence of observations O(1), O(2), . .. O(t), . . . , O(T), where each observation O(t) may be either adiscrete symbol under the VQ approach or a continuous vector. Thesequence of observations may be modeled as a probabilistic function ofan underlying Markov chain having state transitions that are notdirectly observable. In one embodiment, the Markov network is used tomodel a number of user habits and activities. The transitions betweenstates are represented by a transition matrix A=[a(i,j)]. Each a(i,j)term of the transition matrix is the probability of making a transitionto state j given that the model is in state i. The output symbolprobability of the model is represented by a set of functions B=[b(j)(O(t)], where the b(j) (O(t) term of the output symbol matrix is theprobability of outputting observation O(t), given that the model is instate j. The first state is always constrained to be the initial statefor the first time frame of the utterance, as only a prescribed set ofleft to right state transitions are possible. A predetermined finalstate is defined from which transitions to other states cannot occur.Transitions are restricted to reentry of a state or entry to one of thenext two states. Such transitions are defined in the model as transitionprobabilities. Although the preferred embodiment restricts the flowgraphs to the present state or to the next two states, one skilled inthe art can build an HMM model without any transition restrictions,although the sum of all the probabilities of transitioning from anystate must still add up to one. In each state of the model, the currentfeature frame may be identified with one of a set of predefined outputsymbols or may be labeled probabilistically. In this case, the outputsymbol probability b(j) O(t) corresponds to the probability assigned bythe model that the feature frame symbol is O(t). The model arrangementis a matrix A=[a(i,j)] of transition probabilities and a technique ofcomputing B=b(j) O(t), the feature frame symbol probability in state j.The Markov model is formed for a reference pattern from a plurality ofsequences of training patterns and the output symbol probabilities aremultivariate Gaussian function probability densities. The patient habitinformation is processed by a feature extractor. During learning, theresulting feature vector series is processed by a parameter estimator,whose output is provided to the hidden Markov model. The hidden Markovmodel is used to derive a set of reference pattern templates, eachtemplate representative of an identified pattern in a vocabulary set ofreference treatment patterns. The Markov model reference templates arenext utilized to classify a sequence of observations into one of thereference patterns based on the probability of generating theobservations from each Markov model reference pattern template. Duringrecognition, the unknown pattern can then be identified as the referencepattern with the highest probability in the likelihood calculator. TheHMM template has a number of states, each having a discrete value.However, because treatment pattern features may have a dynamic patternin contrast to a single value. The addition of a neural network at thefront end of the HMM in an embodiment provides the capability ofrepresenting states with dynamic values. The input layer of the neuralnetwork comprises input neurons. The outputs of the input layer aredistributed to all neurons in the middle layer. Similarly, the outputsof the middle layer are distributed to all output states, which normallywould be the output layer of the neuron. However, each output hastransition probabilities to itself or to the next outputs, thus forminga modified HMM. Each state of the thus formed HMM is capable ofresponding to a particular dynamic signal, resulting in a more robustHMM. Alternatively, the neural network can be used alone withoutresorting to the transition probabilities of the HMM architecture.

The system allows patients to conduct a low-cost, comprehensive,real-time monitoring of their vital parameters such as ambulation andfalls. Information can be viewed using an Internet-based website, apersonal computer, or simply by viewing a display on the monitor. Datameasured several times each day provide a relatively comprehensive dataset compared to that measured during medical appointments separated byseveral weeks or even months. This allows both the patient and medicalprofessional to observe trends in the data, such as a gradual increaseor decrease in blood pressure, which may indicate a medical condition.The invention also minimizes effects of white coat syndrome since themonitor automatically makes measurements with basically no discomfort;measurements are made at the patient's home or work, rather than in amedical office.

The wearable appliance is small, easily worn by the patient duringperiods of exercise or day-to-day activities, and non-invasivelymeasures blood pressure can be done in a matter of seconds withoutaffecting the patient. An on-board or remote processor can analyze thetime-dependent measurements to generate statistics on a patient's bloodpressure (e.g., average pressures, standard deviation, beat-to-beatpressure variations) that are not available with conventional devicesthat only measure systolic and diastolic blood pressure at isolatedtimes.

The wearable appliance provides an in-depth, cost-effective mechanism toevaluate a patient's health condition. Certain cardiac conditions can becontrolled, and in some cases predicted, before they actually occur.Moreover, data from the patient can be collected and analyzed while thepatient participates in their normal, day-to-day activities.

Software programs associated with the Internet-accessible website,secondary software system, and the personal computer analyze the bloodpressure, and heart rate, and pulse oximetry values to characterize thepatient's cardiac condition. These programs, for example, may provide areport that features statistical analysis of these data to determineaverages, data displayed in a graphical format, trends, and comparisonsto doctor-recommended values.

When the appliance cannot communicate with the mesh network, theappliance simply stores information in memory and continues to makemeasurements. The watch component automatically transmits all the storedinformation (along with a time/date stamp) when it comes in proximity tothe wireless mesh network, which then transmits the information throughthe wireless network.

In one embodiment, the server provides a web services that communicatewith third party software through an interface. To generate vitalparameters such as blood pressure information for the web servicessoftware interface, the patient continuously wears the blood-pressuremonitor for a short period of time, e.g. one to two weeks after visitinga medical professional during a typical ‘check up’ or after signing upfor a short-term monitoring program through the website. In this case,the wearable device such as the watch measures mobility through theaccelerometer and blood pressure in a near-continuous, periodic mannersuch as every fifteen minutes. This information is then transmitted overthe mesh network to a base station that communicates over the Internetto the server.

To view information sent from the blood-pressure monitor and falldetector on the wearable appliance, the patient or an authorized thirdparty such as family members, emergency personnel, or medicalprofessional accesses a patient user interface hosted on the web server200 through the Internet 100 from a remote computer system. The patientinterface displays vital information such as ambulation, blood pressureand related data measured from a single patient. The system may alsoinclude a call center, typically staffed with medical professionals suchas doctors, nurses, or nurse practitioners, whom access a care-providerinterface hosted on the same website on the server 200. Thecare-provider interface displays vital data from multiple patients.

The wearable appliance has an indoor positioning system and processesthese signals to determine a location (e.g., latitude, longitude, andaltitude) of the monitor and, presumably, the patient. This locationcould be plotted on a map by the server, and used to locate a patientduring an emergency, e.g. to dispatch an ambulance.

In one embodiment, the web page hosted by the server 200 includes aheader field that lists general information about the patient (e.g.name, age, and ID number, general location, and information concerningrecent measurements); a table that lists recently measured bloodpressure data and suggested (i.e. doctor-recommended) values of thesedata; and graphs that plot the systolic and diastolic blood pressuredata in a time-dependent manner. The header field additionally includesa series of tabs that each link to separate web pages that include,e.g., tables and graphs corresponding to a different data measured bythe wearable device such as calorie consumption/dissipation, ambulationpattern, sleeping pattern, heart rate, pulse oximetry, and temperature.The table lists a series of data fields that show running average valuesof the patient's daily, monthly, and yearly vital parameters. The levelsare compared to a series of corresponding ‘suggested’ values of vitalparameters that are extracted from a database associated with the website. The suggested values depend on, among other things, the patient'sage, sex, and weight. The table then calculates the difference betweenthe running average and suggested values to give the patient an idea ofhow their data compares to that of a healthy patient. The web softwareinterface may also include security measures such as authentication,authorization, encryption, credential presentation, and digitalsignature resolution. The interface may also be modified to conform toindustry-mandated, XML schema definitions, while being ‘backwardscompatible’ with any existing XML schema definitions.

The system provides for self-registration of appliances by the user.Data can be synchronized between the Repository and appliance(s) via thebase station 20. The user can preview the readings received from theappliance(s) and reject erroneous readings. The user or treatingprofessional can set up the system to generate alerts against receiveddata, based on predefined parameters. The system can determine trends inreceived data, based on user defined parameters.

Appliance registration is the process by which a patient monitoringappliance is associated with one or more users of the system. Thismechanism is also used when provisioning appliances for a user by athird party, such as a clinician (or their respective delegate). In oneimplementation, the user (or delegate) logs into the portal to selectone or more appliances and available for registration. In turn, the basestation server 20 broadcasts a query to all nodes in the mesh network toretrieve identification information for the appliance such asmanufacturer information, appliance model information, appliance serialnumber and optionally a hub number (available on hub packaging). Theuser may register more than one appliance at this point. The systemoptionally sets up a service subscription for appliance(s) usage. Thisincludes selecting service plans and providing payment information. Theappliance(s) are then associated with this user's account and a controlfile with appliance identification information is synchronized betweenthe server 200 and the base station 20 and each appliance oninitialization. In one embodiment, each appliance 8 transmits data tothe base station 20 in an XML format for ease of interfacing and iseither kept encrypted or in a non-readable format on the base station 20for security reasons.

The base station 20 frequently collects and synchronizes data from theappliances 8. The base station 20 may use one of various transportationmethods to connect to the repository on the server 200 using a PC asconduit or through a connection established using an embedded modem(connected to a phone line), a wireless router (DSL or cable wirelessrouter), a cellular modem, or another network-connected appliance (suchas, but not limited to, a web-phone, video-phone, embedded computer, PDAor handheld computer).

In one embodiment, users may set up alerts or reminders that aretriggered when one or more reading meet a certain set of conditions,depending on parameters defined by the user. The user chooses thecondition that they would like to be alerted to and by providing theparameters (e.g. threshold value for the reading) for alert generation.Each alert may have an interval which may be either the number of datapoints or a time duration in units such as hours, days, weeks or months.The user chooses the destination where the alert may be sent. Thisdestination may include the user's portal, e-mail, pager, voice-mail orany combination of the above.

Trends are determined by applying mathematical and statistical rules(e.g. moving average and deviation) over a set of reading values. Eachrule is configurable by parameters that are either automaticallycalculated or are set by the user.

The user may give permission to others as needed to read or edit theirpersonal data or receive alerts. The user or clinician could have a listof people that they want to monitor and have it show on their “MyAccount” page, which serves as a local central monitoring station in oneembodiment. Each person may be assigned different access rights whichmay be more or less than the access rights that the patient has. Forexample, a doctor or clinician could be allowed to edit data for exampleto annotate it, while the patient would have read-only privileges forcertain pages. An authorized person could set the reminders and alertsparameters with limited access to others. In one embodiment, the basestation server 20 serves a web page customized by the user or the user'srepresentative as the monitoring center that third parties such asfamily, physicians, or caregivers can log in and access information. Inanother embodiment, the base station 20 communicates with the server 200at a call center so that the call center provides all services. In yetanother embodiment, a hybrid solution where authorized representativescan log in to the base station server 20 access patient informationwhile the call center logs into both the server 200 and the base stationserver 20 to provide complete care services to the patient.

The server 200 may communicate with a business process outsourcing (BPO)company or a call center to provide central monitoring in an environmentwhere a small number of monitoring agents can cost effectively monitormultiple people 24 hours a day. A call center agent, a clinician or anursing home manager may monitor a group or a number of users via asummary “dashboard” of their readings data, with ability to drill-downinto details for the collected data. A clinician administrator maymonitor the data for and otherwise administer a number of users of thesystem. A summary “dashboard” of readings from all Patients assigned tothe Administrator is displayed upon log in to the Portal by theAdministrator. Readings may be color coded to visually distinguishnormal vs. readings that have generated an alert, along with descriptionof the alert generated. The Administrator may drill down into thedetails for each Patient to further examine the readings data, viewcharts etc. in a manner similar to the Patient's own use of the system.The Administrator may also view a summary of all the appliancesregistered to all assigned Patients, including but not limited to allappliance identification information. The Administrator has access onlyto information about Patients that have been assigned to theAdministrator by a Super Administrator. This allows for segmenting theentire population of monitored Patients amongst multiple Administrators.The Super Administrator may assign, remove and/or reassign Patientsamongst a number of Administrators.

In one embodiment, a patient using an Internet-accessible computer andweb browser, directs the browser to an appropriate URL and signs up fora service for a short-term (e.g., 1 month) period of time. The companyproviding the service completes an accompanying financial transaction(e.g. processes a credit card), registers the patient, and ships thepatient a wearable appliance for the short period of time. Theregistration process involves recording the patient's name and contactinformation, a number associated with the monitor (e.g. a serialnumber), and setting up a personalized website. The patient then usesthe monitor throughout the monitoring period, e.g. while working,sleeping, and exercising. During this time the monitor measures datafrom the patient and wirelessly transmits it through the channel to adata center. There, the data are analyzed using software running oncomputer servers to generate a statistical report. The computer serversthen automatically send the report to the patient using email, regularmail, or a facsimile machine at different times during the monitoringperiod. When the monitoring period is expired, the patient ships thewearable appliance back to the monitoring company.

Different web pages may be designed and accessed depending on theend-user. As described above, individual users have access to web pagesthat only their ambulation and blood pressure data (i.e., the patientinterface), while organizations that support a large number of patients(nursing homes or hospitals) have access to web pages that contain datafrom a group of patients using a care-provider interface. Otherinterfaces can also be used with the web site, such as interfaces usedfor: insurance companies, members of a particular company, clinicaltrials for pharmaceutical companies, and e-commerce purposes. Vitalpatient data displayed on these web pages, for example, can be sortedand analyzed depending on the patient's medical history, age, sex,medical condition, and geographic location. The web pages also support awide range of algorithms that can be used to analyze data once they areextracted from the data packets. For example, an instant message oremail can be sent out as an ‘alert’ in response to blood pressureindicating a medical condition that requires immediate attention.Alternatively, the message could be sent out when a data parameter (e.g.systolic blood pressure) exceeds a predetermined value. In some cases,multiple parameters (e.g., fall detection, positioning data, and bloodpressure) can be analyzed simultaneously to generate an alert message.In general, an alert message can be sent out after analyzing one or moredata parameters using any type of algorithm. These algorithms range fromthe relatively simple (e.g., comparing blood pressure to a recommendedvalue) to the complex (e.g., predictive medical diagnoses using ‘datamining’ techniques). In some cases data may be ‘fit’ using algorithmssuch as a linear or non-linear least-squares fitting algorithm.

In one embodiment, a physician, other health care practitioner, oremergency personnel is provided with access to patient medicalinformation through the server 200. In one embodiment, if the wearableappliance detects that the patient needs help, or if the patient decideshelp is needed, the system can call his or her primary care physician.If the patient is unable to access his or her primary care physician (oranother practicing physician providing care to the patient) a call fromthe patient is received, by an answering service or a call centerassociated with the patient or with the practicing physician. The callcenter determines whether the patient is exhibiting symptoms of anemergency condition by polling vital patient information generated bythe wearable device, and if so, the answering service contacts 911emergency service or some other emergency service. The call center canreview falls information, blood pressure information, and other vitalinformation to determine if the patient is in need of emergencyassistance. If it is determined that the patient in not exhibitingsymptoms of an emergent condition, the answering service may thendetermine if the patient is exhibiting symptoms of a non-urgentcondition. If the patient is exhibiting symptoms of a non-urgentcondition, the answering service will inform the patient that he or shemay log into the server 200 for immediate information on treatment ofthe condition. If the answering service determines that the patient isexhibiting symptoms that are not related to a non-urgent condition, theanswering service may refer the patient to an emergency room, a clinic,the practicing physician (when the practicing physician is available)for treatment.

In another embodiment, the wearable appliance permits direct access tothe call center when the user pushes a switch or button on theappliance, for instance. In one implementation, telephones and switchingsystems in call centers are integrated with the home mesh network toprovide for, among other things, better routing of telephone calls,faster delivery of telephone calls and associated information, andimproved service with regard to client satisfaction throughcomputer-telephony integration (CTI). CTI implementations of variousdesign and purpose are implemented both within individual call-centersand, in some cases, at the telephone network level. For example,processors running CTI software applications may be linked to telephoneswitches, service control points (SCPs), and network entry points withina public or private telephone network. At the call-center level,CTI-enhanced processors, data servers, transaction servers, and thelike, are linked to telephone switches and, in some cases, to similarCTI hardware at the network level, often by a dedicated digital link.CTI processors and other hardware within a call-center is commonlyreferred to as customer premises equipment (CPE). It is the CTIprocessor and application software is such centers that providescomputer enhancement to a call center. In a CTI-enhanced call center,telephones at agent stations are connected to a central telephonyswitching apparatus, such as an automatic call distributor (ACD) switchor a private branch exchange (PBX). The agent stations may also beequipped with computer terminals such as personal computer/video displayunit's (PC/VDU's) so that agents manning such stations may have accessto stored data as well as being linked to incoming callers by telephoneequipment. Such stations may be interconnected through the PC/VDUs by alocal area network (LAN). One or more data or transaction servers mayalso be connected to the LAN that interconnects agent stations. The LANis, in turn, typically connected to the CTI processor, which isconnected to the call switching apparatus of the call center.

When a call from a patient arrives at a call center, whether or not thecall has been pre-processed at an SCP, the telephone number of thecalling line and the medical record are made available to the receivingswitch at the call center by the network provider. This service isavailable by most networks as caller-ID information in one of severalformats such as Automatic Number Identification (ANI). Typically thenumber called is also available through a service such as Dialed NumberIdentification Service (DNIS). If the call center is computer-enhanced(CTI), the phone number of the calling party may be used as a key toaccess additional medical and/or historical information from a customerinformation system (CIS) database at a server on the network thatconnects the agent workstations. In this manner information pertinent toa call may be provided to an agent, often as a screen pop on the agent'sPC/VDU.

The call center enables any of a first plurality of physician or healthcare practitioner terminals to be in audio communication over thenetwork with any of a second plurality of patient wearable appliances.The call center will route the call to a physician or other health carepractitioner at a physician or health care practitioner terminal andinformation related to the patient (such as an electronic medicalrecord) will be received at the physician or health care practitionerterminal via the network. The information may be forwarded via acomputer or database in the practicing physician's office or by acomputer or database associated with the practicing physician, a healthcare management system or other health care facility or an insuranceprovider. The physician or health care practitioner is then permitted toassess the patient, to treat the patient accordingly, and to forwardupdated information related to the patient (such as examination,treatment and prescription details related to the patient's visit to thepatient terminal) to the practicing physician via the network 200.

In one embodiment, the system informs a patient of a practicingphysician of the availability of the web services and referring thepatient to the web site upon agreement of the patient. A call from thepatient is received at a call center. The call center enables physiciansto be in audio communication over the network with any patient wearableappliances, and the call is routed to an available physician at one ofthe physician so that the available physician may carry on a two-wayconversation with the patient. The available physician is permitted tomake an assessment of the patient and to treat the patient. The systemcan forward information related to the patient to a health caremanagement system associated with the physician. The health caremanagement system may be a healthcare management organization, a pointof service health care system, or a preferred provider organization. Thehealth care practitioner may be a nurse practitioner or an internist.

The available health care practitioner can make an assessment of thepatient and to conduct an examination of the patient over the network,including optionally by a visual study of the patient. The system canmake an assessment in accordance with a protocol. The assessment can bemade in accordance with a protocol stored in a database and/or making anassessment in accordance with the protocol may include displaying inreal time a relevant segment of the protocol to the available physician.Similarly, permitting the physician to prescribe a treatment may includepermitting the physician to refer the patient to a third party fortreatment and/or referring the patient to a third party for treatmentmay include referring the patient to one or more of a primary carephysician, specialist, hospital, emergency room, ambulance service orclinic. Referring the patient to a third party may additionally includecommunicating with the third party via an electronic link included in arelevant segment of a protocol stored in a protocol database resident ona digital storage medium and the electronic link may be a hypertextlink. When a treatment is being prescribed by a physician, the systemcan communicate a prescription over the network to a pharmacy and/orcommunicating the prescription over the network to the pharmacy mayinclude communicating to the pharmacy instructions to be given to thepatient pertaining to the treatment of the patient. Communicating theprescription over the network to the pharmacy may also includecommunicating the prescription to the pharmacy via a hypertext linkincluded in a relevant segment of a protocol stored in a databaseresident on a digital storage medium. In accordance with another relatedembodiment, permitting the physician to conduct the examination may beaccomplished under conditions such that the examination is conductedwithout medical instruments at the patient terminal where the patient islocated.

In another embodiment, a system for delivering medical examination,diagnosis, and treatment services from a physician to a patient over anetwork includes a first plurality of health care practitioners at aplurality of terminals, each of the first plurality of health carepractitioner terminals including a display device that shows informationcollected by the wearable appliances and a second plurality of patientterminals or wearable appliances in audiovisual communication over anetwork with any of the first plurality of health care practitionerterminals. A call center is in communication with the patient wearableappliances and the health care practitioner terminals, the call centerrouting a call from a patient at one of the patient terminals to anavailable health care practitioner at one of the health carepractitioner terminals, so that the available health care practitionermay carry on a two-way conversation with the patient. A protocoldatabase resident on a digital storage medium is accessible to each ofthe health care practitioner terminals. The protocol database contains aplurality of protocol segments such that a relevant segment of theprotocol may be displayed in real time on the display device of thehealth care practitioner terminal of the available health carepractitioner for use by the available health care practitioner in makingan assessment of the patient. The relevant segment of the protocoldisplayed in real time on the display device of the health carepractitioner terminal may include an electronic link that establishescommunication between the available health care practitioner and a thirdparty and the third party may be one or more of a primary carephysician, specialist, hospital, emergency room, ambulance service,clinic or pharmacy.

In accordance with other related embodiment, the patient wearableappliance may include establish a direct connection to the call centerby pushing a button on the appliance. Further, the protocol database maybe resident on a server that is in communication with each of the healthcare practitioner terminals and each of the health care practitionerterminals may include a local storage device and the protocol databaseis replicated on the local storage device of one or more of thephysician terminals.

In another embodiment, a system for delivering medical examination,diagnosis, and treatment services from a physician to a patient over anetwork includes a first plurality of health care practitionerterminals, each of the first plurality of health care practitionerterminals including a display device and a second plurality of patientterminals in audiovisual communication over a network with any of thefirst plurality of health care practitioner terminals. Each of thesecond plurality of patient terminals includes a camera having pan, tiltand zoom modes, such modes being controlled from the first plurality ofhealth care practitioner terminals. A call center is in communicationwith the patient terminals and the health care practitioner terminalsand the call center routes a call from a patient at one of the patientterminals to an available health care practitioner at one of the healthcare practitioner terminals, so that the available health carepractitioner may carry on a two-way conversation with the patient andvisually observe the patient.

In one embodiment, the information is store in a secure environment,with security levels equal to those of online banking, social securitynumber input, and other confidential information. Conforming to HealthInsurance Portability and Accountability Act (HIPAA) requirements, thesystem creates audit trails, requires logins and passwords, and providesdata encryption to ensure the patient information is private and secure.The HIPAA privacy regulations ensure a national floor of privacyprotections for patients by limiting the ways that health plans,pharmacies, hospitals and other covered entities can use patients'personal medical information. The regulations protect medical recordsand other individually identifiable health information, whether it is onpaper, in computers or communicated orally.

Due to its awareness of the patient's position, the server 200 canoptionally control a mobility assistance device such as a smart cane orrobot. The robotic smart cane sends video from its camera to the server20, which in turn coordinates the position of the robot, as determinedby the cameras 10 mounted in the home as well as the robot camera. Therobot position, as determined by the server 20, is then transmitted tothe robot for navigation. The robot has a frame with an extended handle.The handle includes handle sensors mounted thereon to detect the forceplaces on each handle to receive as input the movement desired by thepatient. In one embodiment, the robot has a control navigation systemthat accepts patient command as well as robot self-guidance command. Themobility is a result of give-and-take between the patient'sself-propulsion and the walker's automated reactions. Thus, when thepatient moves the handle to the right, the robot determines that thepatient is interested in turning and actuates the drive systemsappropriately. However, if the patient is turning into an obstacle, asdetermined by the cameras and the server 20, the drive system providesgentle resistance that tells the patient of an impending collision.

If, for example, a patient does not see a coffee table ahead, the walkerwill detect it, override the patient's steering to avoid it, and therebyprevent a possible fall. Onboard software processes the data from 180degrees of approaching terrain and steers the front wheel towardopenings and away from obstacles.

The control module executes software that enables the robot to movearound its environment safely. The software performs localization,mapping, path planning and obstacle avoidance. In one embodiment, imagesfrom a plurality of wall-mounted cameras 10 are transmitted to theserver 20. The server 20 collects images of the robot and triangulatesthe robot position by cross-referencing the images. The information isthen correlated with the image from the robot-mounted camera and opticalencoders that count the wheel rotations to calculate traveled distancefor range measurement. In this process, a visual map of unique“landmarks” created as the robot moves along its path is annotated withthe robot's position to indicate the position estimate of the landmark.The current image, seen from the robot, is compared with the images inthe database to find matching landmarks. Such matches are used to updatethe position of the robot according to the relative position of thematching landmark. By repeatedly updating the position of landmarksbased on new data, the software incrementally improves the map bycalculating more accurate estimates for the position of the landmarks.An improved map results in more accurate robot position estimates.Better position estimates contribute to better estimates for thelandmark positions and so on. If the environment changes so much thatthe robot no longer recognizes previous landmarks, the robotautomatically updates the map with new landmarks. Outdated landmarksthat are no longer recognized can easily be deleted from the map bysimply determining if they were seen or matched when expected.

Using the obstacle avoidance algorithm, the robot generates correctivemovements to avoid obstacles not represented in the path planner such asopen/closed doors, furniture, people, and more. The robot rapidlydetects obstacles using its sensors and controls its speed and headingto avoid obstacles.

The hazard avoidance mechanisms provide a reflexive response tohazardous situations to insure the robot's safety and guarantee that itdoes not damage itself or the environment. Mechanisms for hazardavoidance include collision detection using not one but a complementaryset of sensors and techniques. For instance, collision avoidance can beprovided using contact sensing, motor load sensing, and vision. Thecombination of multiple sources for collision detection guarantees safecollision avoidance. Collision detection provides a last resort fornegotiating obstacles in case obstacle avoidance fails to do so in thefirst place, which can be caused by moving objects or software andhardware failures.

If the walker is in motion (as determined by the wheel encoder), theforce applied to the brake pads is inversely proportional to thedistance to obstacles. If the walker is stopped, the brakes should befully applied to provide a stable base on which the patient can rest.When the walker is stopped and the patient wishes to move again, thebrakes should come off slowly to prevent the walker from lurchingforward

The walker should mostly follow the patient's commands, as this iscrucial for patient acceptance. For the safety braking and the safetybraking and steering control systems, the control system only influencesthe motion when obstacles or cliffs are near the patient. In otherwords, the walker is, typically, fully patient controlled. For all othersituations, the control system submits to the patient's desire. Thisdoes not mean that the control system shuts down, or does not providethe usual safety features. In fact, all of the control systems fall backon their emergency braking to keep the patient safe. When the controlsystem has had to brake to avoid an obstacle or has given up trying tolead the patient on a particular path, the patient must disengage thebrakes (via a pushbutton) or re-engage the path following (again via apushbutton) to regain control or allow collaboration again. This letsthe patient select the walker's mode manually when they disagree withthe control system's choices.

FIG. 5 shows an exemplary process to monitor patient. First, the processsets up mesh network appliances (1000). Next, the process determinespatient position using in-door positioning system (1002). The processthen determines patient movement using accelerometer output (1004).Sharp accelerations may be used to indicate fall. Further, the z axisaccelerometer changes can indicate the height of the appliance from thefloor and if the height is near zero, the system infers that the patienthad fallen. The system can also determine vital parameter includingpatient heart rate (1006). The system determines if patient needsassistance based on in-door position, fall detection and vital parameter(1008). If a fall is suspected, the system confirms the fall bycommunicating with the patient prior to calling a third party such asthe patient's physician, nurse, family member, 911, 511, 411, or a paidcall center to get assistance for the patient (1010). If confirmed or ifthe patient is non-responsive, the system contacts the third party andsends voice over mesh network to appliance on the patient to allow oneor more third parties to talk with the patient (1012). If needed, thesystem calls and/or conferences emergency personnel into the call(1014).

In one embodiment, if the patient is outside of the mesh network rangesuch as when the user is traveling away from his/her home, the systemcontinuously records information into memory until the home mesh networkis reached or until the monitoring appliance reaches an internet accesspoint. While the wearable appliance is outside of the mesh networkrange, the device searches for a cell phone with an expansion cardplugged into a cell phone expansion slot such as the SDIO slot. If thewearable appliance detects a cell phone that is mesh network compatible,the wearable appliance communicates with the cell phone and providesinformation to the server 200 using the cellular connection. In oneembodiment, a Zigbee SDIO card from C-guys, Inc., enablesdevice-to-device communications for PDAs and smart phones. C-guys'ZigBee SDIO card includes the company's CG-100 SDIO applicationinterface controller, which is designed to convert an application signalto an SD signal (or vice versa). The ZigBee card can provide signalranges of up to 10 m in the 2.4 GHz band and data rates of up to 200kbps. The card has peer-to-peer communications mode and supports directapplication to PDAs or any SD supported hand-held cell phones. In thisembodiment, the PDA or cell phone can provide a GPS position informationinstead of the indoor position information generated by the mesh networkappliances 8. The cell phone GPS position information, accelerometerinformation and vital information such as heart rate information istransmitted using the cellular channel to the server 200 for processingas is normal. In another embodiment where the phone works through WiFi(802.11) or WiMAX (802.16) or ultra-wideband protocol instead of thecellular protocol, the wearable appliance can communicate over theseprotocols using a suitable mesh network interface to the phone. Ininstances where the wearable appliance is outside of its home base and adangerous condition such as a fall is detected, the wearable appliancecan initiate a distress call to the authorized third party usingcellular, WiFi, WiMAX, or UWB protocols as is available.

FIG. 6A shows a portable embodiment of the present invention where thevoice recognizer is housed in a wrist-watch. As shown in FIG. 6, thedevice includes a wrist-watch sized case 1380 supported on a wrist band1374. The case 1380 may be of a number of variations of shape but can beconveniently made a rectangular, approaching a box-like configuration.The wrist-band 1374 can be an expansion band or a wristwatch strap ofplastic, leather or woven material. The processor or CPU of the wearableappliance is connected to a radio frequency (RF) transmitter/receiver(such as a Bluetooth device, a Zigbee device, a WiFi device, a WiMAXdevice, or an 802.X transceiver, among others.

In one embodiment, the back of the device is a conductive metalelectrode 1381 that in conjunction with a second electrode 1383 mountedon the wrist band 1374, enables differential EKG or ECG to be measured.The electrical signal derived from the electrodes is typically 1 mVpeak-peak. In one embodiment where only one electrode 1381 or 1383 isavailable, an amplification of about 1000 is necessary to render thissignal usable for heart rate detection. In the embodiment withelectrodes 1381 and 1383 available, a differential amplifier is used totake advantage of the identical common mode signals from the EKG contactpoints, the common mode noise is automatically cancelled out using amatched differential amplifier. In one embodiment, the differentialamplifier is a Texas Instruments INA321 instrumentation amplifier thathas matched and balanced integrated gain resistors. This device isspecified to operate with a minimum of 2.7V single rail power supply.The INA321 provides a fixed amplification of 5× for the EKG signal. Withits CMRR specification of 94 dB extended up to 3 KHz the INA321 rejectsthe common mode noise signals including the line frequency and itsharmonics. The quiescent current of the INA321 is 40 mA and the shutdown mode current is less than 1 mA. The amplified EKG signal isinternally fed to the on chip analog to digital converter. The ADCsamples the EKG signal with a sampling frequency of 512 Hz. Precisesampling period is achieved by triggering the ADC conversions with atimer that is clocked from a 32.768 kHz low frequency crystaloscillator. The sampled EKG waveform contains some amount of superimposed line frequency content. This line frequency noise is removed bydigitally filtering the samples. In one implementation, a 17-tap lowpass FIR filter with pass band upper frequency of 6 Hz and stop bandlower frequency of 30 Hz is implemented in this application. The filtercoefficients are scaled to compensate the filter attenuation and provideadditional gain for the EKG signal at the filter output. This adds up toa total amplification factor of greater than 1000× for the EKG signal.

The wrist band 1374 can also contain other electrical devices such asultrasound transducer, optical transducer or electromagnetic sensors,among others. In one embodiment, the transducer is an ultrasonictransducer that generates and transmits an acoustic wave upon commandfrom the CPU during one period and listens to the echo returns during asubsequent period. In use, the transmitted bursts of sonic energy arescattered by red blood cells flowing through the subject's radialartery, and a portion of the scattered energy is directed back towardthe ultrasonic transducer 84. The time required for the return energy toreach the ultrasonic transducer varies according to the speed of soundin the tissue and according to the depth of the artery. Typical transittimes are in the range of 6 to 7 microseconds. The ultrasonic transduceris used to receive the reflected ultrasound energy during the dead timesbetween the successive transmitted bursts. The frequency of theultrasonic transducer's transmit signal will differ from that of thereturn signal, because the scattering red blood cells within the radialartery are moving. Thus, the return signal, effectively, is frequencymodulated by the blood flow velocity.

A driving and receiving circuit generates electrical pulses which, whenapplied to the transducer, produce acoustic energy having a frequency onthe order of 8 MHz, a pulse width or duration of approximately 8microseconds, and a pulse repetition interval (PRI) of approximately 16μs, although other values of frequency, pulse width, and PRI may beused. In one embodiment, the transducer 84 emits an 8 microsecond pulse,which is followed by an 8 microsecond “listen” period, every 16microseconds. The echoes from these pulses are received by theultrasonic transducer 84 during the listen period. The ultrasonictransducer can be a ceramic piezoelectric device of the type well knownin the art, although other types may be substituted.

An analog signal representative of the Doppler frequency of the echo isreceived by the transducer and converted to a digital representation bythe ADC, and supplied to the CPU for signal processing. Within the CPU,the digitized Doppler frequency is scaled to compute the blood flowvelocity within the artery based on the Doppler frequency. Based on thereal time the blood flow velocity, the CPU applies the vital model tothe corresponding blood flow velocity to produce the estimated bloodpressure value.

Prior to operation, calibration is done using a calibration device andthe monitoring device to simultaneously collect blood pressure values(systolic, diastolic pressures) and a corresponding blood flow velocitygenerated by the monitoring device. The calibration device is attachedto the base station and measures systolic and diastolic blood pressureusing a cuff-based blood pressure monitoring device that includes amotor-controlled pump and data-processing electronics. While thecuff-based blood pressure monitoring device collects patient data, thetransducer collects patient data in parallel and through the watch'sradio transmitter, blood flow velocity is sent to the base station forgenerating a computer model that converts the blood flow velocityinformation into systolic and diastolic blood pressure values and thisinformation is sent wirelessly from the base station to the watch fordisplay and to a remote server if needed. This process is repeated at alater time (e.g., 15 minutes later) to collect a second set ofcalibration parameters. In one embodiment, the computer model fits theblood flow velocity to the systolic/diastolic values. In anotherembodiment, the computer trains a neural network or HMM to recognize thesystolic and diastolic blood pressure values.

After the computer model has been generated, the system is ready forreal-time blood pressure monitoring. In an acoustic embodiment, thetransducer directs ultrasound at the patient's artery and subsequentlylistens to the echos therefrom. The echoes are used to determine bloodflow, which is fed to the computer model to generate the systolic anddiastolic pressure values as well as heart rate value. The CPU's outputsignal is then converted to a form useful to the user such as a digitalor analog display, computer data file, or audible indicator. The outputsignal can drive a speaker to enable an operator to hear arepresentation of the Doppler signals and thereby to determine when thetransducer is located approximately over the radial artery. The outputsignal can also be wirelessly sent to a base station for subsequentanalysis by a physician, nurse, caregiver, or treating professional. Theoutput signal can also be analyzed for medical attention and medicaltreatment.

It is noted that while the above embodiment utilizes a preselected pulseduration of 8 microseconds and pulse repetition interval of 16microseconds, other acoustic sampling techniques may be used inconjunction with the invention. For example, in a second embodiment ofthe ultrasonic driver and receiver circuit (not shown), the acousticpulses are range-gated with a more complex implementation of the gatelogic. As is well known in the signal processing arts, range-gating is atechnique by which the pulse-to-pulse interval is varied based on thereceipt of range information from earlier emitted and reflected pulses.Using this technique, the system may be “tuned” to receive echoesfalling within a specific temporal window which is chosen based on therange of the echo-producing entity in relation to the acoustic source.The delay time before the gate is turned on determines the depth of thesample volume. The amount of time the gate is activated establishes theaxial length of the sample volume. Thus, as the acoustic source (in thiscase the ultrasonic transducer 84) is tuned to the echo-producing entity(red blood cells, or arterial walls), the pulse repetition interval isshortened such that the system may obtain more samples per unit time,thereby increasing its resolution. It will be recognized that otheracoustic processing techniques may also be used, all of which areconsidered to be equivalent.

In one optical embodiment, the transducer can be an optical transducer.The optical transducer can be a light source and a photo-detectorembedded in the wrist band portions 1374. The light source can belight-emitting diodes that generate red (λ^(˜)630 nm) and infrared(λ^(˜)900 nm) radiation, for example. The light source and thephoto-detector are slidably adjustable and can be moved along the wristband to optimize beam transmission and pick up. As the heart pumps bloodthrough the patient's finger, blood cells absorb and transmit varyingamounts of the red and infrared radiation depending on how much oxygenbinds to the cells' hemoglobin. The photo-detector detects transmissionat the predetermined wavelengths, for example red and infraredwavelengths, and provides the detected transmission to a pulse-oximetrycircuit embedded within the wrist-watch. The output of thepulse-oximetry circuit is digitized into a time-dependent opticalwaveform, which is then sent back to the pulse-oximetry circuit andanalyzed to determine the user's vital signs.

In the electromagnetic sensor embodiment, the wrist band 1374 is aflexible plastic material incorporated with a flexible magnet. Themagnet provides a magnetic field, and one or more electrodes similar toelectrode 1383 are positioned on the wrist band to measure voltage dropswhich are proportional to the blood velocity. The electromagneticembodiment may be mounted on the upper arm of the patient, on the ankleor on the neck where peripheral blood vessels pass through and theirblood velocity may be measured with minimal interruptions. The flexiblemagnet produces a pseudo-uniform (non-gradient) magnetic field. Themagnetic field can be normal to the blood flow direction when wrist band1374 is mounted on the user's wrist or may be a rotative pseudo-uniformmagnetic field so that the magnetic field is in a transversal directionin respect to the blood flow direction. The electrode output signals areprocessed to obtain a differential measurement enhancing the signal tonoise ratio. The flow information is derived based on the periodicity ofthe signals. The decoded signal is filtered over several periods andthen analyzed for changes used to estimate artery and vein blood flow.Systemic stroke volume and cardiac output may be calculated from theperipheral SV index value.

The wrist-band 1374 further contains an antenna 1376 for transmitting orreceiving radio frequency signals. The wristband 1374 and the antenna1376 inside the band are mechanically coupled to the top and bottomsides of the wrist-watch housing 1380. Further, the antenna 1376 iselectrically coupled to a radio frequency transmitter and receiver forwireless communications with another computer or another user. Althougha wrist-band is disclosed, a number of substitutes may be used,including a belt, a ring holder, a brace, or a bracelet, among othersuitable substitutes known to one skilled in the art. The housing 1380contains the processor and associated peripherals to provide thehuman-machine interface. A display 1382 is located on the front sectionof the housing 1380. A speaker 1384, a microphone 1388, and a pluralityof push-button switches 1386 and 1390 are also located on the frontsection of housing 1380.

The electronic circuitry housed in the watch case 1380 detects adverseconditions such as falls or seizures. In one implementation, thecircuitry can recognize speech, namely utterances of spoken words by theuser, and converting the utterances into digital signals. The circuitryfor detecting and processing speech to be sent from the wristwatch tothe base station 20 over the mesh network includes a central processingunit (CPU) connected to a ROM/RAM memory via a bus. The CPU is apreferably low power 16-bit or 32-bit microprocessor and the memory ispreferably a high density, low-power RAM. The CPU is coupled via the busto processor wake-up logic, one or more accelerometers to detect suddenmovement in a patient, an ADC 102 which receives speech input from themicrophone. The ADC converts the analog signal produced by themicrophone into a sequence of digital values representing the amplitudeof the signal produced by the microphone at a sequence of evenly spacedtimes. The CPU is also coupled to a digital to analog (D/A) converter,which drives the speaker to communicate with the user. Speech signalsfrom the microphone are first amplified, pass through an antialiasingfilter before being sampled. The front-end processing includes anamplifier, a bandpass filter to avoid antialiasing, and ananalog-to-digital (A/D) converter or a CODEC. To minimize space, theADC, the DAC and the interface for wireless transceiver and switches maybe integrated into one integrated circuit to save space. In oneembodiment, the wrist watch acts as a walkie-talkie so that voice isreceived over the mesh network by the base station 20 and then deliveredto a call center over the POTS or PSTN network. In another embodiment,voice is provided to the call center using the Internet through suitableVOIP techniques. In one embodiment, speech recognition such as a speechrecognizer is discussed in U.S. Pat. No. 6,070,140 by the inventor ofthe instant invention, the content of which is incorporated byreference.

FIG. 6B shows an exemplary mesh network working with the wearableappliance of FIG. 6A. Data collected and communicated on the display1382 of the watch as well as voice is transmitted to a base station 1390for communicating over a network to an authorized party 1394. The watchand the base station is part of a mesh network that may communicate witha medicine cabinet to detect opening or to each medicine container 1391to detect medication compliance. Other devices include mesh networkthermometers, scales, or exercise devices. The mesh network alsoincludes a plurality of home/room appliances 1392-1399. The ability totransmit voice is useful in the case the patient has fallen down andcannot walk to the base station 1390 to request help. Hence, in oneembodiment, the watch captures voice from the user and transmits thevoice over the Zigbee mesh network to the base station 1390. The basestation 1390 in turn dials out to an authorized third party to allowvoice communication and at the same time transmits the collected patientvital parameter data and identifying information so that help can bedispatched quickly, efficiently and error-free. In one embodiment, thebase station 1390 is a POTS telephone base station connected to thewired phone network. In a second embodiment, the base station 1390 canbe a cellular telephone connected to a cellular network for voice anddata transmission. In a third embodiment, the base station 1390 can be aWiMAX or 802.16 standard base station that can communicate VOIP and dataover a wide area network. Alternatively, the base station cancommunicate over POTS and a wireless network such as cellular or WiMAXor both.

In one embodiment, the processor and transceiver on the watch and thebase station conform to the Zigbee protocol. ZigBee is a cost-effective,standards-based wireless networking solution that supports lowdata-rates, low-power consumption, security, and reliability. Singlechip Zigbee controllers with wireless transceivers built-in include theChipcon/Ember CC2420: Single-chip 802.15.4 radio transceiver and theFreeScale single chip Zigbee and microcontroller. In variousembodiments, the processor communicates with a Z axis accelerometermeasures the patient's up and down motion and/or an X and Y axisaccelerometer measures the patient's forward and side movements. In oneembodiment, EKG and/or blood pressure parameters can be captured by theprocessor. The controllers upload the captured data when the memory isfull or while in wireless contact with other Zigbee nodes.

The wristwatch device can also be used to control home automation. Theuser can have flexible management of lighting, heating and coolingsystems from anywhere in the home. The watch automates control ofmultiple home systems to improve conservation, convenience and safety.The watch can capture highly detailed electric, water and gas utilityusage data and embed intelligence to optimize consumption of naturalresources. The system is convenient in that it can be installed,upgraded and networked without wires. The patient can receive automaticnotification upon detection of unusual events in his or her home. Forexample, if smoke or carbon monoxide detectors detect a problem, thewrist-watch can buzz or vibrate to alert the user and the central hubtriggers selected lights to illuminate the safest exit route.

In another embodiment, the watch serves a key fob allowing the user towirelessly unlock doors controlled by Zigbee wireless receiver. In thisembodiment, when the user is within range, the door Zigbee transceiverreceives a request to unlock the door, and the Zigbee transceiver on thedoor transmits an authentication request using suitable securitymechanism. Upon entry, the Zigbee doorlock device sends access signalsto the lighting, air-conditioning and entertainment systems, amongothers. The lights and temperature are automatically set topre-programmed preferences when the user's presence is detected.

Although Zigbee is mentioned as an exemplary protocol, other protocolssuch as UWB, Bluetooth, WiFi and WiMAX can be used as well.

While the foregoing addresses the needs of the elderly, the system canassist infants as well. Much attention has been given to ways to reducea risk of dying from Sudden Infant Death Syndrome (SIDS), an afflictionwhich threatens infants who have died in their sleep for heretoforeunknown reasons. Many different explanations for this syndrome and waysto prevent the syndrome are found in the literature. It is thought thatinfants which sleep on their backs may be at risk of death because ofthe danger of formula regurgitation and liquid aspiration into thelungs. It has been thought that infants of six (6) months or less do nothave the motor skills or body muscular development to regulate movementsresponsive to correcting breathing problems that may occur during sleep.

In an exemplary system to detect and minimize SIDS problem in an infantpatient, a diaper pad is used to hold an array of integrated sensors andthe pad can be placed over a diaper, clothing, or blanket. Theintegrated sensors can provide data for measuring position, temperature,sound, vibration, movement, and optionally other physical propertiesthrough additional sensors. Each pad can have sensors that provide oneor more of the above data. The sensors can be added or removed asnecessary depending on the type of data being collected.

The sensor should be water proof and disposable. The sensor can beswitch on/off locally or remotely. The sensor can be removable or clipon easily. The sensor can store or beam out information for analysispurpose, e.g. store body temperature every 5 seconds. The sensor can beturn-on for other purposed, e.g. diaper wet, it will beep and allow ababy care provider to take care of the business in time. The array ofsensors can be self selective, e.g., when one sensor can detect strongheart beat, it will turn off others to do so.

The sensor can be used for drug delivery system, e.g. when patient hasabdomen pain, soothing drug can be applied, based on the level of painthe sensor detects, different dose of drugs will be applied.

The array of sensors may allow the selection and analysis of zones ofsensors in the areas of interest such as the abdomen area. Each sensorarray has a low spatial resolution: approximately 10 cm between eachsensor. In addition to lower cost due to the low number of sensors, itis also possible to modify the data collection rate from certain sensorsthat are providing high-quality data. Other sensors may include thoseworn on the body, such as in watch bands, finger rings, or adhesivesensors, but telemetry, not wires, would be used to communicate with thecontroller.

The sensor can be passive device such as a reader, which mounted nearthe crib can active it from time to time. In any emergency situation,the sensor automatically signals a different state which the reader candetect.

The sensor can be active and powered by body motion or body heat. Thesensor can detect low battery situation and warn the user to provide areplacement battery. In one embodiment, a plurality of sensors attachedto the infant collects the vital parameters. For example, the sensorscan be attached to the infant's clothing (shirt or pant), diaper,undergarment or bed sheet, bed linen, or bed spread.

The patient may wear one or more sensors, for example devices forsensing ECG, EKG, blood pressure, sugar level, weight, temperature andpressure, among others. In one embodiment, an optical temperature sensorcan be used. In another embodiment, a temperature thermistor can be usedto sense patient temperature. In another embodiment, a fat scale sensorcan be used to detect the patient's fat content. In yet anotherembodiment, a pressure sensor such as a MEMS sensor can be used to sensepressure on the patient.

In one embodiment, the sensors are mounted on the patient's wrist (suchas a wristwatch sensor) and other convenient anatomical locations.Exemplary sensors include standard medical diagnostics for detecting thebody's electrical signals emanating from muscles (EMG and EOG) and brain(EEG) and cardiovascular system (ECG). Leg sensors can includepiezoelectric accelerometers designed to give qualitative assessment oflimb movement. Additionally, thoracic and abdominal bands used tomeasure expansion and contraction of the thorax and abdomenrespectively. A small sensor can be mounted on the subject's finger inorder to detect blood-oxygen levels and pulse rate. Additionally, amicrophone can be attached to throat and used in sleep diagnosticrecordings for detecting breathing and other noise. One or more positionsensors can be used for detecting orientation of body (lying on leftside, right side or back) during sleep diagnostic recordings. Each ofsensors can individually transmit data to the server 20 using wired orwireless transmission. Alternatively, all sensors can be fed through acommon bus into a single transceiver for wired or wireless transmission.The transmission can be done using a magnetic medium such as a floppydisk or a flash memory card, or can be done using infrared or radionetwork link, among others.

In one embodiment, the sensors for monitoring vital signs are enclosedin a wrist-watch sized case supported on a wrist band. The sensors canbe attached to the back of the case. For example, in one embodiment,Cygnus' AutoSensor (Redwood City, Calif.) is used as a glucose sensor. Alow electric current pulls glucose through the skin. Glucose isaccumulated in two gel collection discs in the AutoSensor. TheAutoSensor measures the glucose and a reading is displayed by the watch.

In another embodiment, EKG/ECG contact points are positioned on the backof the wrist-watch case. In yet another embodiment that providescontinuous, beat-to-beat wrist arterial pulse rate measurements, apressure sensor is housed in a casing with a ‘free-floating’ plunger asthe sensor applanates the radial artery. A strap provides a constantforce for effective applanation and ensuring the position of the sensorhousing to remain constant after any wrist movements. The change in theelectrical signals due to change in pressure is detected as a result ofthe piezoresistive nature of the sensor are then analyzed to arrive atvarious arterial pressure, systolic pressure, diastolic pressure, timeindices, and other blood pressure parameters.

The heartbeat detector can be one of: EKG detector, ECG detector,optical detector, ultrasonic detector, or microphone/digital stethoscopefor picking up heart sound. In one embodiment, one EKG/ECG contact pointis provided on the back of the wrist watch case and one or more EKG/ECGcontact points are provided on the surface of the watch so that when auser's finger or skin touches the contact points, an electrical signalindicative of heartbeat activity is generated. An electrocardiogram(ECG) or EKG is a graphic tracing of the voltage generated by thecardiac or heart muscle during a heartbeat. It provides very accurateevaluation of the performance of the heart. The heart generates anelectrochemical impulse that spreads out in the heart in such a fashionas to cause the cells to contract and relax in a timely order and thusgive the heart a pumping characteristic. This sequence is initiated by agroup of nerve cells called the sinoatrial (SA) node resulting in apolarization and depolarization of the cells of the heart. Because thisaction is electrical in nature and because the body is conductive withits fluid content, this electrochemical action can be measured at thesurface of the body. An actual voltage potential of approximately 1 mVdevelops between various body points. This can be measured by placingelectrode contacts on the body. The four extremities and the chest wallhave become standard sites for applying the electrodes. Standardizingelectrocardiograms makes it possible to compare them as taken fromperson to person and from time to time from the same person. The normalelectrocardiogram shows typical upward and downward deflections thatreflect the alternate contraction of the atria (the two upper chambers)and of the ventricles (the two lower chambers) of the heart. Thevoltages produced represent pressures exerted by the heart muscles inone pumping cycle. The first upward deflection, P, is due to atriacontraction and is known as the atrial complex. The other deflections,Q, R, S, and T, are all due to the action of the ventricles and areknown as the ventricular complexes. Any deviation from the norm in aparticular electrocardiogram is indicative of a possible heart disorder.

The CPU measures the time duration between the sequential pulses andconverts each such measurement into a corresponding timing measurementindicative of heart rate. The CPU also processes a predetermined numberof most recently occurring timing measurements in a prescribed fashion,to produce an estimate of heartbeat rate for display on a display deviceon the watch and/or for transmission over the wireless network. Thisestimate is updated with the occurrence of each successive pulse.

In one embodiment, the CPU produces the estimate of heartbeat rate byfirst averaging a plurality of measurements, then adjusting theparticular one of the measurements that differs most from the average tobe equal to that average, and finally computing an adjusted averagebased on the adjusted set of measurements. The process may repeat theforegoing operations a number of times so that the estimate of heartbeatrate is substantially unaffected by the occurrence of heartbeatartifacts.

In one EKG or ECG detector, the heartbeat detection circuitry includes adifferential amplifier for amplifying the signal transmitted from theEKG/ECG electrodes and for converting it into single-ended form, and abandpass filter and a 60 Hz notch filter for removing background noise.The CPU measures the time durations between the successive pulses andestimates the heartbeat rate. The time durations between the successivepulses of the pulse sequence signal provides an estimate of heartbeatrate. Each time duration measurement is first converted to acorresponding rate, preferably expressed in beats per minute (bpm), andthen stored in a file, taking the place of the earliest measurementpreviously stored. After a new measurement is entered into the file, thestored measurements are averaged, to produce an average ratemeasurement. The CPU optionally determines which of the storedmeasurements differs most from the average, and replaces thatmeasurement with the average.

Upon initiation, the CPU increments a period timer used in measuring thetime duration between successive pulses. This timer is incremented insteps of about two milliseconds in one embodiment. It is then determinedwhether or not a pulse has occurred during the previous twomilliseconds. If it has not, the CPU returns to the initial step ofincrementing the period timer. If a heartbeat has occurred, on the otherhand, the CPU converts the time duration measurement currently stored inthe period timer to a corresponding heartbeat rate, preferably expressedin bpm. After the heartbeat rate measurement is computed, the CPUdetermines whether or not the computed rate is intermediate prescribedthresholds of 20 bpm and 240 bpm. If it is not, it is assumed that thedetected pulse was not in fact a heartbeat and the period timer iscleared.

In an optical heartbeat detector embodiment, an optical transducer ispositioned on a finger, wrist, or ear lobe. The ear, wrist or fingerpulse oximeter waveform is then analyzed to extract the beat-to-beatamplitude, area, and width (half height) measurements. The oximeterwaveform is used to generate heartbeat rate in this embodiment. In oneimplementation, a reflective sensor such as the Honeywell HLC1395 can beused. The device emits lights from a window in the infrared spectrum andreceives reflected light in a second window. When the heart beats, bloodflow increases temporarily and more red blood cells flow through thewindows, which increases the light reflected back to the detector. Thelight can be reflected, refracted, scattered, and absorbed by one ormore detectors. Suitable noise reduction is done, and the resultingoptical waveform is captured by the CPU.

In another optical embodiment, blood pressure is estimated from theoptical reading using a mathematical model such as a linear correlationwith a known blood pressure reading. In this embodiment, the pulseoximeter readings are compared to the blood-pressure readings from aknown working blood pressure measurement device during calibration.Using these measurements the linear equation is developed relatingoximeter output waveform such as width to blood-pressure (systolic, meanand pulse pressure). In one embodiment, a transform (such as a Fourieranalysis or a Wavelet transform) of the oximeter output can be used togenerate a model to relate the oximeter output waveform to the bloodpressure. Other non-linear math model or relationship can be determinedto relate the oximeter waveform to the blood pressure.

In one implementation, the pulse oximeter probe and a blood pressurecuff are placed on the corresponding contralateral limb to theoscillometric (Dinamap 8100; Critikon, Inc, Tampa, Fla., USA) cuff site.The pulse oximeter captures data on plethysmographic waveform, heartrate, and oxygen saturation. Simultaneous blood pressure measurementswere obtained from the oscillometric device, and the pulse oximeter.Systolic, diastolic, and mean blood pressures are recorded from theoscillometric device. This information is used derive calibrationparameters relating the pulse oximeter output to the expected bloodpressure. During real time operation, the calibration parameters areapplied to the oximeter output to predict blood pressure in a continuousor in a periodic fashion. In yet another embodiment, the device includesan accelerometer or alternative motion-detecting device to determinewhen the patient' hand is at rest, thereby reducing motion-relatedartifacts introduced to the measurement during calibration and/oroperation. The accelerometer can also function as a falls detectiondevice.

In an ultrasonic embodiment, a piezo film sensor element is placed onthe wristwatch band. The sensor can be the SDT1-028K made by MeasurementSpecialties, Inc. The sensor should have features such as: (a) it issensitive to low level mechanical movements, (b) it has an electrostaticshield located on both sides of the element (to minimize 50/60 Hz ACline interference), (c) it is responsive to low frequency movements inthe 0.7-12 Hz range of interest. A filter/amplifier circuit has athree-pole low pass filter with a lower (−3 dB) cutoff frequency atabout 12-13 Hz. The low-pass filter prevents unwanted 50/60 Hz AC lineinterference from entering the sensor. However, the piezo film elementhas a wide band frequency response so the filter also attenuates anyextraneous sound waves or vibrations that get into the piezo element.The DC gain is about +30 dB.

Waveform averaging can be used to reduce noise. It reinforces thewaveform of interest by minimizing the effect of any random noise. Thesepulses were obtained when the arm was motionless. If the arm was movedwhile capturing the data the waveform did not look nearly as clean.That's because motion of the arm causes the sonic vibrations to enterthe piezo film through the arm or by way of the cable. An accelerometeris used to detect arm movement and used to remove inappropriate datacapture.

In one embodiment that can determine blood pressure, two piezo filmsensors and filter/amplifier circuits can be configured as anon-invasive velocity type blood pressure monitor. One sensor can be onthe wrist and the other can be located on the inner left elbow at thesame location where Korotkoff sounds are monitored during traditionalblood pressure measurements with a spygmometer. The correlation betweenpulse delay and blood pressure is well known in the art of non-invasiveblood pressure monitors.

In yet another embodiment, an ultrasonic transducer generates andtransmits an acoustic wave into the user's body such as the wrist orfinger. The transducer subsequently receives pressure waves in the formof echoes resulting from the transmitted acoustic waves. In oneembodiment, an ultrasonic driving and receiving circuit generateselectrical pulses which, when applied to the transducer produce acousticenergy having a frequency on the order of 8 MHz, a pulse width orduration of approximately 8 microseconds, and a pulse repetitioninterval (PRI) of approximately 16 microseconds, although other valuesof frequency, pulse width, and PRI may be used. Hence, the transduceremits an 8 microsecond ultrasonic pulse, which is followed by an 8microsecond “listen” period, every 16 microseconds. The echoes fromthese pulses are received by the ultrasonic transducer during the listenperiod. The ultrasonic transducer can be a ceramic piezoelectric deviceof the type well known in the art, although other types may besubstituted. The transducer converts the received acoustic signal to anelectrical signal, which is then supplied to the receiving section ofthe ultrasonic driver and receiver circuit 616, which contains tworeceiver circuits. The output of the first receiver circuit is an analogsignal representative of the Doppler frequency of the echo received bythe transducer which is digitized and supplied to the CPU. Within theCPU, the digitized Doppler frequency is scaled to compute the bloodvelocity within the artery based on the Doppler frequency. Thetime-frequency distribution of the blood velocity is then computed.Finally, the CPU maps in time the peak of the time-frequencydistribution to the corresponding pressure waveform to produce theestimated mean arterial pressure (MAP). The output of the ultrasonicreceiver circuit is an analog echo signal proportional to absorption ofthe transmitted frequencies by blood or tissue. This analog signal isdigitized and process so that each group of echoes, generated for adifferent transversal position, is integrated to determine a mean value.The mean echo values are compared to determine the minimum value, whichis caused by direct positioning over the artery. In one embodiment, thedevice includes an accelerometer or alternative motion-detecting deviceto determine when the patient' hand is at rest, thereby reducingmotion-related artifacts introduced to the measurement.

In yet another ultrasonic embodiment, a transducer includes a first anda second piezoelectric crystal, wherein the crystals are positioned atan angle to each other, and wherein the angle is determined based on thedistance of the transducer to the living subject. The firstpiezoelectric crystal is energized by an original ultrasonic frequencysignal, wherein the original ultrasonic frequency signal is reflectedoff the living subject and received by the second piezoelectric crystal.More specifically, the system includes a pair of piezoelectric crystalsat an angle to each other, wherein the angle is determined by the depthof the object being monitored. If the object is the radial artery of ahuman subject (e.g., adult, infant), the angle of the two crystals withrespect to the direction of the blood flow would be about 5 to about 20degrees. One of the crystals is energized at an ultrasonic frequency.The signal is then reflected back by the user's wrist and picked up bythe second crystal. The frequency received is either higher or lowerthan the original frequency depending upon the direction and the speedof the fluidic mass flow. For example, when blood flow is monitored, thedirection of flow is fixed. Thus, the Doppler frequency which is thedifference between the original and the reflected frequency depends onlyupon the speed of the blood flow. Ultrasonic energy is delivered to oneof the two piezoelectric elements in the module by the power amplifier.The other element picks up the reflected ultrasonic signal as Dopplerfrequencies.

In a digital stethoscope embodiment, a microphone or a piezoelectrictransducer is placed near the wrist artery to pick up heart rateinformation. In one embodiment, the microphone sensor and optionally theEKG sensor are place on the wrist band 1374 of the watch to analyze theacoustic signal or signals emanating from the cardiovascular system and,optionally can combine the sound with an electric signal (EKG) emanatingfrom the cardiovascular system and/or an acoustic signal emanating fromthe respiratory system. The system can perform automated auscultation ofthe cardiovascular system, the respiratory system, or both. For example,the system can differentiate pathological from benign heart murmurs,detect cardiovascular diseases or conditions that might otherwise escapeattention, recommend that the patient go through for a diagnostic studysuch as an echocardiography or to a specialist, monitor the course of adisease and the effects of therapy, decide when additional therapy orintervention is necessary, and providing a more objective basis for thedecision(s) made. In one embodiment, the analysis includes selecting oneor more beats for analysis, wherein each beat comprises an acousticsignal emanating from the cardiovascular system; performing atime-frequency analysis of beats selected for analysis so as to provideinformation regarding the distribution of energy, the relativedistribution of energy, or both, over different frequency ranges at oneor more points in the cardiac cycle; and processing the information toreach a clinically relevant conclusion or recommendation. In anotherimplementation, the system selects one or more beats for analysis,wherein each beat comprises an acoustic signal emanating from thecardiovascular system; performs a time-frequency analysis of beatsselected for analysis so as to provide information regarding thedistribution of energy, the relative distribution of energy, or both,over different frequency ranges at one or more points in the cardiaccycle; and present information derived at least in part from theacoustic signal, wherein the information comprises one or more itemsselected from the group consisting of: a visual or audio presentation ofa prototypical beat, a display of the time-frequency decomposition ofone or more beats or prototypical beats, and a playback of the acousticsignal at a reduced rate with preservation of frequency content.

In an electromagnetic embodiment where the wrist band incorporates aflexible magnet to provide a magnetic field and one or more electrodespositioned on the wrist band to measure voltage drops which areproportional to the blood velocity, instantaneously variation of theflow can be detected but not artery flow by itself. To estimate the flowof blood in the artery, the user or an actuator such as motorized cufftemporarily stops the blood flow in the vein by applying externalpressure or by any other method. During the period of time in which thevein flow is occluded, the decay of the artery flow is measured. Thismeasurement may be used for zeroing the sensor and may be used in amodel for estimating the steady artery flow. The decay in artery flowdue to occlusion of veins is measured to arrive at a model the rate ofartery decay. The system then estimates an average artery flow beforeocclusion. The blood flow can then be related to the blood pressure.

In another embodiment, an ionic flow sensor is used with a drivingelectrode that produces a pulsatile current. The pulsatile currentcauses a separation of positive and negative charges that flows in theblood of the arteries and veins passing in the wrist area. Usingelectrophoresis principle, the resistance of the volume surrounded bythe source first decreases and then increases. The difference inresistance in the blood acts as a mark that moves according to the flowof blood so that marks are flowing in opposite directions by arteriesand veins.

In the above embodiments, accelerometer information is used to detectthat the patient is at rest prior to making a blood pressure measurementand estimation. Further, a temperature sensor may be incorporated sothat the temperature is known at any minute. The processor correlatesthe temperature measurement to the blood flow measurement forcalibration purposes.

In another embodiment, the automatic identification of the first,second, third and fourth heart sounds (S1, S2, S3, S4) is done. In yetanother embodiment, based on the heart sound, the system analyzes thepatient for mitral valve prolapse. The system performs a time-frequencyanalysis of an acoustic signal emanating from the subject'scardiovascular system and examines the energy content of the signal inone or more frequency bands, particularly higher frequency bands, inorder to determine whether a subject suffers from mitral valve prolapse.

FIG. 7 shows an exemplary mesh network that includes the wrist-watch ofFIG. 6 in communication with a mesh network including a telephone suchas a wired telephone as well as a cordless telephone. In one embodiment,the mesh network is an IEEE 802.15.4 (ZigBee) network. IEEE 802.15.4defines two device types; the reduced function device (RFD) and the fullfunction device (FFD). In ZigBee these are referred to as the ZigBeePhysical Device types. In a ZigBee network a node can have three roles:ZigBee Coordinator, ZigBee Router, and ZigBee End Device. These are theZigBee Logical Device types. The main responsibility of a ZigBeeCoordinator is to establish a network and to define its main parameters(e.g. choosing a radio-frequency channel and defining a unique networkidentifier). One can extend the communication range of a network byusing ZigBee Routers. These can act as relays between devices that aretoo far apart to communicate directly. ZigBee End Devices do notparticipate in routing. An FFD can talk to RFDs or other FFDs, while anRFD can talk only to an FFD. An RFD is intended for applications thatare extremely simple, such as a light switch or a passive infraredsensor; they do not have the need to send large amounts of data and mayonly associate with a single FFD at a time. Consequently, the RFD can beimplemented using minimal resources and memory capacity and have lowercost than an FFD. An FFD can be used to implement all three ZigBeeLogical Device types, while an RFD can take the role as an End Device.

One embodiment supports a multicluster-multihop network assembly toenable communication among every node in a distribution of nodes. Thealgorithm should ensure total connectivity, given a network distributionthat will allow total connectivity. One such algorithm of an embodimentis described in U.S. Pat. No. 6,832,251, the content of which isincorporated by referenced. The '251 algorithm runs on each nodeindependently. Consequently, the algorithm does not have globalknowledge of network topology, only local knowledge of its immediateneighborhood. This makes it well suited to a wide variety ofapplications in which the topology may be time-varying, and the numberof nodes may be unknown. Initially, all nodes consider themselvesremotes on cluster zero. The assembly algorithm floods one packet(called an assembly packet) throughout the network. As the packet isflooded, each node modifies it slightly to indicate what the next nodeshould do. The assembly packet tells a node whether it is a base or aremote, and to what cluster it belongs. If a node has seen an assemblypacket before, it will ignore all further assembly packets.

The algorithm starts by selecting (manually or automatically) a startnode. For example, this could be the first node to wake up. This startnode becomes a base on cluster 1, and floods an assembly packet to allof its neighbors, telling them to be remotes on cluster 1. These remotesin turn tell all their neighbors to be bases on cluster 2. Only nodesthat have not seen an assembly packet before will respond to thisrequest, so nodes that already have decided what to be will not changetheir status. The packet continues on, oscillating back and forthbetween “become base/become remote”, and increasing the cluster numbereach time. Since the packet is flooded to all neighbors at every step,it will reach every node in the network. Because of the oscillatingnature of the “become base/become remote” instructions, no two baseswill be adjacent. The basic algorithm establishes a multi-clusternetwork with all gateways between clusters, but self-assembly time isproportional with the size of the network. Further, it includes onlysingle hop clusters. Many generalizations are possible, however. If manynodes can begin the network nucleation, all that is required toharmonize the clusters is a mechanism that recognizes precedence (e.g.,time of nucleation, size of subnetwork), so that conflicts in boundaryclusters are resolved. Multiple-hop clusters can be enabled by means ofestablishing new clusters from nodes that are N hops distant from themaster.

Having established a network in this fashion, the masters can beoptimized either based on number of neighbors, or other criteria such asminimum energy per neighbor communication. Thus, the basic algorithm isat the heart of a number of variations that lead to a scalablemulti-cluster network that establishes itself in time, and that isnearly independent of the number of nodes, with clusters arrangedaccording to any of a wide range of optimality criteria. Networksynchronism is established at the same time as the network connections,since the assembly packet(s) convey timing information outwards fromconnected nodes.

The network nodes can be mesh network appliances to provide voicecommunications, home security, door access control, lighting control,power outlet control, dimmer control, switch control, temperaturecontrol, humidity control, carbon monoxide control, fire alarm control,blind control, shade control, window control, oven control, cookingrange control, personal computer control, entertainment console control,television control, projector control, garage door control, car control,pool temperature control, water pump control, furnace control, heatercontrol, thermostat control, electricity meter monitor, water metermonitor, gas meter monitor, or remote diagnostics. The telephone can beconnected to a cellular telephone to answer calls directed at thecellular telephone. The connection can be wired or wireless usingBluetooth or ZigBee. The telephone synchronizes calendar, contact,emails, blogs, or instant messaging with the cellular telephone.Similarly, the telephone synchronizes calendar, contact, emails, blogs,or instant messaging with a personal computer. A web server cancommunicate with the Internet through the POTS to provide information toan authorized remote user who logs into the server. A wireless routersuch as 802.11 router, 802.16 router, WiFi router, WiMAX router,Bluetooth router, ×10 router can be connected to the mesh network.

A mesh network appliance can be connected to a power line to communicate×10 data to and from the mesh network. ×10 is a communication protocolthat allows up to 256×10 products to talk to each other using theexisting electrical wiring in the home. Typically, the installation issimple, a transmitter plugs (or wires) in at one location in the homeand sends its control signal (on, off, dim, bright, etc.) to a receiverwhich plugs (or wires) into another location in the home. The meshnetwork appliance translates messages intended for ×10 device to berelayed over the ZigBee wireless network, and then transmitted over thepower line using a ZigBee to ×10 converter appliance.

An in-door positioning system links one or more mesh network appliancesto provide location information. Inside the home or office, the radiofrequency signals have negligible multipath delay spread (for timingpurposes) over short distances. Hence, radio strength can be used as abasis for determining position. Alternatively, time of arrival can beused to determine position, or a combination of radio signal strengthand time of arrival can be used. Position estimates can also be achievedin an embodiment by beamforming, a method that exchanges time-stampedraw data among the nodes. While the processing is relatively morecostly, it yields processed data with a higher signal to noise ratio(SNR) for subsequent classification decisions, and enables estimates ofangles of arrival for targets that are outside the convex hull of theparticipating sensors. Two such clusters of ZigBee nodes can thenprovide for triangulation of distant targets. Further, beamformingenables suppression of interfering sources, by placing nulls in thesynthetic beam pattern in their directions. Another use of beamformingis in self-location of nodes when the positions of only a very smallnumber of nodes or appliances are known such as those sensors nearestthe wireless stations. In one implementation where each node knows thedistances to its neighbors due to their positions, and some smallfraction of the nodes (such as those nearest a PC with GPS) of thenetwork know their true locations. As part of the network-buildingprocedure, estimates of the locations of the nodes that lie within ornear the convex hull of the nodes with known position can be quicklygenerated. To start, the shortest distance (multihop) paths aredetermined between each reference node. All nodes on this path areassigned a location that is the simple linear average of the tworeference locations, as if the path were a straight line. A node whichlies on the intersection of two such paths is assigned the average ofthe two indicated locations. All nodes that have been assigned locationsnow serve as references. The shortest paths among these new referencenodes are computed, assigning locations to all intermediate nodes asbefore, and continuing these iterations until no further nodes getassigned locations. This will not assign initial position estimates toall sensors. The remainder can be assigned locations based on pairwiseaverages of distances to the nearest four original reference nodes. Someconsistency checks on location can be made using trigonometry and onefurther reference node to determine whether or not the node likely lieswithin the convex hull of the original four reference sensors.

In two dimensions, if two nodes have known locations, and the distancesto a third node are known from the two nodes, then trigonometry can beused to precisely determine the location of the third node. Distancesfrom another node can resolve any ambiguity. Similarly, simple geometryproduces precise calculations in three dimensions given four referencenodes. But since the references may also have uncertainty, analternative procedure is to perform a series of iterations wheresuccessive trigonometric calculations result only in a delta of movementin the position of the node. This process can determine locations ofnodes outside the convex hull of the reference sensors. It is alsoamenable to averaging over the positions of all neighbors, since therewill often be more neighbors than are strictly required to determinelocation. This will reduce the effects of distance measurement errors.Alternatively, the network can solve the complete set of equations ofintersections of hyperbola as a least squares optimization problem.

In yet another embodiment, any or all of the nodes may includetransducers for acoustic, infrared (IR), and radio frequency (RF)ranging. Therefore, the nodes have heterogeneous capabilities forranging. The heterogeneous capabilities further include differentmargins of ranging error. Furthermore, the ranging system is re-used forsensing and communication functions. For example, wideband acousticfunctionality is available for use in communicating, bistatic sensing,and ranging. Such heterogeneous capability of the sensors 40 can providefor ranging functionality in addition to communications functions. Asone example, repeated use of the communications function improvesposition determination accuracy over time. Also, when the ranging andthe timing are conducted together, they can be integrated in aself-organization protocol in order to reduce energy consumption.Moreover, information from several ranging sources is capable of beingfused to provide improved accuracy and resistance to environmentalvariability. Each ranging means is exploited as a communication means,thereby providing improved robustness in the presence of noise andinterference. Those skilled in the art will realize that there are manyarchitectural possibilities, but allowing for heterogeneity from theoutset is a component in many of the architectures.

Turning now to FIGS. 8-13, various exemplary monitoring devices areshown. In FIG. 8, a ring 130 has an opening 132 for transmitting andreceiving acoustic energy to and from the sensor 84 in an acousticimplementation. In an optical implementation, a second opening (notshown) is provided to emit an optical signal from an LED, for example,and an optical detector can be located at the opening 132 to receive theoptical signal passing through the finger wearing the ring 130. Inanother implementation, the ring has an electrically movable portion 134and rigid portions 136-138 connected thereto. The electrically movableportion 134 can squeeze the finger as directed by the CPU during anapplanation sweep to determine the arterial blood pressure.

FIG. 9 shows an alternate finger cover embodiment where a finger-mountedmodule housing the photo-detector and light source. The finger mountedmodule can be used to measure information that is processed to determinethe user's blood pressure by measuring blood flow in the user's fingerand sending the information through a wireless connection to the basestation. In one implementation, the housing is made from a flexiblepolymer material.

In an embodiment to be worn on the patient's ear lobe, the monitoringdevice can be part of an earring jewelry clipped to the ear lobe. In theimplementation of FIG. 10, the monitoring device has a jewelry body 149that contains the monitoring electronics and power source. The surfaceof the body 149 is an ornamental surface such as jade, ivory, pearl,silver, or gold, among others. The body 149 has an opening 148 thattransmits energy such as optical or acoustic energy through the ear lobeto be detected by a sensor 144 mounted on a clamp portion that issecured to the body 149 at a base 147. The energy detected through thesensor 144 is communicated through an electrical connector to theelectronics in the jewelry body 149 for processing the received energyand for performing wireless communication with a base station. In FIG.2E, a bolt 145 having a stop end 146 allows the user to adjust thepressure of the clamp against the ear lobe. In other implementations, aspring biased clip is employed to retain the clip on the wearer's earlobe. A pair of members, which snap together under pressure, arecommonly used and the spring pressure employed should be strong enoughto suit different thicknesses of the ear lobe.

FIGS. 11 and 12 show two additional embodiments of the monitoringdevice. In FIG. 11, a wearable monitoring device is shown. Themonitoring device has a body 160 comprising microphone ports 162, 164and 170 arranged in a first order noise cancelling microphonearrangement. The microphones 162 and 164 are configured to optimallyreceive distant noises, while the microphone 170 is optimized forcapturing the user's speech. A touch sensitive display 166 and aplurality of keys 168 are provided to capture hand inputs. Further, aspeaker 172 is provided to generate a verbal feedback to the user.

Turning now to FIG. 12, a jewelry-sized monitoring device isillustrated. In this embodiment, a body 172 houses a microphone port 174and a speaker port 176. The body 172 is coupled to the user via thenecklace 178 so as to provide a personal, highly accessible personalcomputer. Due to space limitations, voice input/output is an importantuser interface of the jewelry-sized computer. Although a necklace isdisclosed, one skilled in the art can use a number of other substitutessuch as a belt, a brace, a ring, or a band to secure the jewelry-sizedcomputer to the user.

FIG. 13 shows an exemplary ear phone embodiment 180. The ear phone 180has an optical transmitter 182 which emits LED wavelengths that arereceived by the optical receiver 184. The blood oximetry information isgenerated and used to determine blood pulse or blood pressure.Additionally, a module 186 contains mesh network communicationelectronics, accelerometer, and physiological sensors such as EKG/ECGsensors or temperature sensors or ultrasonic sensors. In addition, aspeaker (not shown) is provided to enable voice communication over themesh network, and a microphone 188 is provided to pick up voice duringverbal communication and pick up heart sound when the user is not usingthe microphone for voice communication. The ear phone optionally has anear canal temperature sensor for sensing temperature in a human.

FIG. 14 shows an exemplary adhesive patch embodiment. The patch may beapplied to a persons skin by anyone including the person themselves oran authorized person such as a family member or physician. The adhesivepatch is shown generally at 190 having a gauze pad 194 attached to oneside of a backing 192, preferably of plastic, and wherein the pad canhave an impermeable side 194 coating with backing 192 and a module 196which contains electronics for communicating with the mesh network andfor sensing acceleration and EKG/ECG, heart sound, microphone, opticalsensor, or ultrasonic sensor in contacts with a wearer's skin. In oneembodiment, the module 196 has a skin side that may be coated with aconductive electrode lotion or gel to improve the contact. The entirepatch described above may be covered with a plastic or foil strip toretain moisture and retard evaporation by a conductive electrode lotionor gel provided improve the electrode contact. In one embodiment, anacoustic sensor (microphone or piezoelectric sensor) and an electricalsensor such as EKG sensor contact the patient with a conductive gelmaterial. The conductive gel material provides transmissioncharacteristics so as to provide an effective acoustic impedance matchto the skin in addition to providing electrical conductivity for theelectrical sensor. The acoustic transducer can be directed mounted onthe conductive gel material substantially with or without anintermediate air buffer. The entire patch is then packaged as sterile asare other over-the-counter adhesive bandages. When the patch is wornout, the module 196 may be removed and a new patch backing 192 may beused in place of the old patch. One or more patches may be applied tothe patient's body and these patches may communicate wirelessly usingthe mesh network or alternatively they may communicate through apersonal area network using the patient's body as a communicationmedium.

The term “positional measurement,” as that term is used herein, is notlimited to longitude and latitude measurements, or to metes and bounds,but includes information in any form from which geophysical positionscan be derived. These include, but are not limited to, the distance anddirection from a known benchmark, measurements of the time required forcertain signals to travel from a known source to the geophysicallocation where the signals may be electromagnetic or other forms, ormeasured in terms of phase, range, Doppler or other units.

FIG. 15A shows a system block diagram of the network-based patientmonitoring system in a hospital or nursing home setting. The system hasa patient component 215, a server component 216, and a client component217. The patient component 215 has one or more mesh network patienttransmitters 202 for transmitting data to the central station. Thecentral server comprises one or more Web servers 205, one or morewaveform servers 204 and one or more mesh network receivers 211. Theoutput of each mesh network receiver 211 is connected to at least one ofthe waveform servers 204. The waveform servers 204 and Web the servers205 are connected to the network 105. The Web servers 205 are alsoconnected to a hospital database 230. The hospital database 230 containspatient records. In the embodiment of FIG. 15A, a plurality of nursestations provide a plurality of nurse computer user interface 208. Theuser interface 208 receives data from an applet 210 that communicateswith the waveform server 204 and updates the display of the nursecomputers for treating patients.

The network client component 217 comprises a series of workstations 106connected to the network 105. Each workstation 106 runs a World Wide Web(WWW or Web) browser application 208. Each Web browser can open a pagethat includes one or more media player applets 210. The waveform servers204 use the network 105 to send a series of messages 220 to the Webservers 205. The Web servers 205 use the network 105 to communicatemessages, shown as a path 221, to the workstations 106. The media playerapplets running on the workstations 106 use the network 105 to sendmessages over a path 223 directly to the waveform servers 204.

FIG. 15B shows a variation of the system of FIG. 15A for call centermonitoring. In this embodiment, the patient appliances 202 wirelesslycommunicate to home base stations (not shown) which are connected to thePOTS or PSTN network for voice as well as data transmission. The data iscaptured by the waveform server 204 and the voice is passed through tothe call center agent computer 207 where the agent can communicate byvoice with the patient. The call center agent can forward the call to aprofessional such as a nurse or doctor or emergency service personnel ifnecessary. Hence, the system can include a patient monitoring appliancecoupled to the POTS or PSTN through the mesh network. The patientmonitoring appliance monitors drug usage and patient falls. The patientmonitoring appliance monitors patient movement. A call center can callto the telephone to provide a human response.

In one exemplary monitoring service providing system, such as anemergency service providing system, the system includes a communicationnetwork (e.g., the Public Switch Telephone Network or PSTN or POTS), awide area communication network (e.g., TCP/IP network) in call centers.The communication network receives calls destined for one of the callcenters. In this regard, each call destined for one of the call centersis preferably associated with a particular patient, a call identifier ora call identifier of a particular set of identifiers. A call identifierassociated with an incoming call may be an identifier dialed orotherwise input by the caller. For example, the call centers may belocations for receiving calls from a particular hospital or nursinghome.

To network may analyze the automatic number information (ANI) and/orautomatic location information (ALI) associated with the call. In thisregard, well known techniques exist for analyzing the ANI and ALI of anincoming call to identify the call as originating from a particularcalling device or a particular calling area. Such techniques may beemployed by the network to determine whether an incoming call originatedfrom a calling device within an area serviced by the call centers.Moreover, if an incoming call originated from such an area and if theincoming call is associated with the particular call identifier referredto above, then the network preferably routes the call to a designatedfacility.

When a call is routed to the facility, a central data manager, which maybe implemented in software, hardware, or a combination thereof,processes the call according to techniques that will be described inmore detail hereafter and routes the call, over the wide area network,to one of the call centers depending on the ANI and/or ALI associatedwith the call. In processing the call, the central data manager mayconvert the call from one communication protocol to anothercommunication protocol, such as voice over internet protocol (VoIP), forexample, in order to increase the performance and/or efficiency of thesystem. The central data manager may also gather information to help thecall centers in processing the call. There are various techniques thatmay be employed by the central data manager to enhance the performanceand/or efficiency of the system, and examples of such techniques will bedescribed in more detail hereafter.

Various benefits may be realized by utilizing a central facility tointercept or otherwise receive a call from the network and to then routethe call to one of the call centers via WAN. For example, servingmultiple call centers with a central data manager, may help to reducetotal equipment costs. In this regard, it is not generally necessary toduplicate the processing performed by the central data manager at eachof the call centers. Thus, equipment at each of the call centers may bereduced. As more call centers are added, the equipment savings enabledby implementing equipment at the central data manager instead of thecall centers generally increases. Furthermore, the system is notdependent on any telephone company's switch for controlling the mannerin which data is communicated to the call centers. In this regard, thecentral data manager may receive a call from the network and communicatethe call to the destination call centers via any desirable communicationtechnique, such as VoIP, for example. Data security is another possiblebenefit of the exemplary system 10 as the central data manager is ableto store the data for different network providers associated withnetwork on different partitions.

While the patient interface 90 (FIG. 1A) can provide information for asingle person, FIG. 15C shows an exemplary interface to monitor aplurality of persons, while FIG. 15D shows an exemplary dash-board thatprovides summary information on the status of a plurality of persons. Asshown in FIG. 1C, for professional use such as in hospitals, nursinghomes, or retirement homes, a display can track a plurality of patients.In FIG. 15C, a warning (such as sound or visual warning in the form oflight or red flashing text) can be generated to point out the particularpatient that may need help or attention. In FIG. 15D, a magnifier glasscan be dragged over a particular individual icon to expand and showdetailed vital parameters of the individual and if available, imagesfrom the camera 10 trained on the individual for real time videofeedback. The user can initiate voice communication with the user forconfirmation purposes by clicking on a button provided on the interfaceand speaking into a microphone on the professional's workstation.

In one embodiment for professional users such as hospitals and nursinghomes, a Central Monitoring Station provides alarm and vital signoversight for a plurality of patients from a single computerworkstation. FIG. 15E shows an exemplary multi-station vital parameteruser interface for a professional embodiment, while FIG. 15F shows anexemplary trending pattern display. The clinician interface uses simplepoint and click actions with a computer mouse or trackball. Theclinician can initiate or change monitoring functions from either theCentral Station or the bedside monitor. One skilled in the art willrecognize that patient data such as EKG data can be shown either by ascrolling waveform that moves along the screen display, or by a movingbar where the waveform is essentially stationary and the bar movesacross the screen.

In one embodiment, software for the professional monitoring systemprovides a login screen to enter user name and password, together withdatabase credentials. In Select Record function, the user can select aperson, based on either entered or pre-selected criteria. From herenavigate to their demographics, medical record, etc. The system can showa persons demographics, includes aliases, people involved in their care,friends and family, previous addresses, home and work locations,alternative numbers and custom fields. The system can show all dataelements of a person's medical record. These data elements are not ‘hardwired’, but may be configured in the data dictionary to suit yourparticular requirements. It is possible to create views of the recordthat filter it to show (for instance) just the medications or diagnosis,etc. Any data element can be can be designated ‘plan able’ in the datadictionary and then scheduled. A Summary Report can be done. Example ofa report displayed in simple format, selecting particular elements anddates. As many of these reports as required can be created, going acrossall data in the system based on some criteria, with a particularselection of fields and sorting, grouping and totaling criteria. Reportscan be created that can format and analyze any data stored on theserver. The system supports OLE controls and can include graphs, barcodes, etc. These can be previewed on screen, printed out or exported ina wide variety of formats. The system also maintains a directory of allorganizations the administrator wishes to record as well as your own.These locations are then used to record the location for elements of themedical record (where applicable), work addresses for people involved inthe care and for residential addresses for people in residential care.The data elements that form the medical record are not ‘hard wired’ (iepredefined) but may be customized by the users to suit current andfuture requirements.

In one embodiment, the wearable appliance can store patient data in itsdata storage device such as flash memory. The data can includeImmunizations and dates; medications (prescriptions and supplements);physician names, addresses, phone numbers, email addresses; location anddetails of advance directives; insurance company, billing address, phonenumber, policy number; emergency contacts, addresses,home/business/pager phone numbers, email addresses. The data can includecolor or black and white photo of the wearer of the device; a thumbprint, iris print of other distinguishing physical characteristic;dental records; sample ECG or Cardiac Echo Scan.; blood type; presentmedication being taken; drug interaction precautions; drug and/orallergic reaction precautions; a description of serious preexistingmedical conditions; Emergency Medical Instructions, which could include:administering of certain suggested drugs or physical treatments; callingemergency physician numbers listed; bringing the patient to a certaintype of clinic or facility based on religious beliefs; and living willinstructions in the case of seriously ill patients; Organ Donorinstructions; Living Will instructions which could include: instructionsfor life support or termination of treatment; notification of next ofkin and/or friends including addresses and telephone numbers; ECG trace;Cardiac Echo Scan; EEG trace; diabetes test results; x-ray scans, amongothers. The wearable appliance stores the wearer's medical records andID information. In one embodiment, to start the process new/originalmedical information is organized and edited to fit into the BWD pageformat either in physicians office or by a third party with access to apatient's medical records using the base unit storage and encryptingsoftware which can be stored in a normal pc or other compatible computerdevice. The system can encrypt the records so as to be secure andconfidential and only accessible to authorized individuals withcompatible de-encrypting software. In the event the wearer is strickenwith an emergency illness a Paramedic, EMT or Emergency Room Techniciancan use a wireless interrogator to rapidly retrieve and display thestored medical records in the wearable appliance and send the medicalrecords via wireless telemetry to a remote emergency room or physician'soffice for rapid and life-saving medical intervention in a crisissituation. In a Non-emergency Situation, the personal health informationservice is also helpful as it eliminates the hassle of repeatedlyfilling out forms when changing health plans or seeing a new physician;stores vaccination records to schools or organizations without callingthe pediatrician; or enlists the doctor's or pharmacist's advice aboutmultiple medications without carrying all the bottles to a personalvisit.

In one embodiment, a plurality of body worn sensors with in-doorpositioning can be used as an Emergency Department and Urgent CareCenter Tracking System. The system tracks time from triage to MDassessment, identifies patients that have not yet been registered,records room usage, average wait time, and average length of stay. Thesystem allows user defined “activities” so that hospitals can tracktimes and assist in improving patient flow and satisfaction. The systemcan set custom alerts and send email/pager notifications to betteridentify long patient wait times and record the number of these alertoccurrences. The system can manage room usage by identifying those roomswhich are under/over utilized. The hospital administrator can set manualor automatic alerts and generate custom reports for analysis of patientflow. The system maximizes revenue by streamlining processes andimproving throughput; improves charge capture by ensuring compliancewith regulatory standards; increases accountability by collecting clear,meaningful data; enhances risk management and QA; and decreasesliability.

FIG. 16A shows ant exemplary process to continuously determine bloodpressure of a patient. The process generates a blood pressure model of apatient (2002); determines a blood flow velocity using a piezoelectrictransducer (2004); and provides the blood flow velocity to the bloodpressure model to continuously estimate blood pressure (2006).

FIG. 16B shows another exemplary process to continuously determine bloodpressure of a patient. First, during an initialization mode, amonitoring device and calibration device are attached to patient (2010).The monitoring device generates patient blood flow velocity, whileactual blood pressure is measured by a calibration device (2012). Next,the process generates a blood pressure model based on the blood flowvelocity and the actual blood pressure (2014). Once this is done, thecalibration device can be removed (2016). Next, during an operationmode, the process periodically samples blood flow velocity from themonitoring device on a real-time basis (18) and provides the blood flowvelocity as input information to the blood pressure model to estimateblood pressure (20). This process can be done in continuously orperiodically as specified by a user.

In one embodiment, to determine blood flow velocity, acoustic pulses aregenerated and transmitted into the artery using an ultrasonic transducerpositioned near a wrist artery. These pulses are reflected by variousstructures or entities within the artery (such as the artery walls, andthe red blood cells within the subject's blood), and subsequentlyreceived as frequency shifts by the ultrasonic transducer. Next, theblood flow velocity is determined. In this process, the frequencies ofthose echoes reflected by blood cells within the blood flowing in theartery differ from that of the transmitted acoustic pulses due to themotion of the blood cells. This well known “Doppler shift” in frequencyis used to calculate the blood flow velocity. In one embodiment fordetermining blood flow velocity, the Doppler frequency is used todetermine mean blood velocity. For example, U.S. Pat. No. 6,514,211, thecontent of which is incorporated by reference, discusses blood flowvelocity using a time-frequency representation.

In one implementation, the system can obtain one or more numericalcalibration curves describing the patient's vital signs such as bloodpressure. The system can then direct energy such as infrared orultrasound at the patient's artery and detecting reflections thereof todetermine blood flow velocity from the detected reflections. The systemcan numerically fit or map the blood flow velocity to one or morecalibration parameters describing a vital-sign value. The calibrationparameters can then be compared with one or more numerical calibrationcurves to determine the blood pressure.

Additionally, the system can analyze blood pressure, and heart rate, andpulse oximetry values to characterize the user's cardiac condition.These programs, for example, may provide a report that featuresstatistical analysis of these data to determine averages, data displayedin a graphical format, trends, and comparisons to doctor-recommendedvalues.

In one embodiment, feed forward artificial neural networks (NNs) areused to classify valve-related heart disorders. The heart sounds arecaptured using the microphone or piezoelectric transducer. Relevantfeatures were extracted using several signal processing tools, discretewavelet transfer, fast fourier transform, and linear prediction coding.The heart beat sounds are processed to extract the necessary featuresby: a) denoising using wavelet analysis, b) separating one beat out ofeach record c) identifying each of the first heart sound (FHS) and thesecond heart sound (SHS). Valve problems are classified according to thetime separation between the FHS and th SHS relative to cardiac cycletime, namely whether it is greater or smaller than 20% of cardiac cycletime. In one embodiment, the NN comprises 6 nodes at both ends, with onehidden layer containing 10 nodes. In another embodiment, linearpredictive code (LPC) coefficients for each event were fed to twoseparate neural networks containing hidden neurons.

In another embodiment, a normalized energy spectrum of the sound data isobtained by applying a Fast Fourier Transform. The various spectralresolutions and frequency ranges were used as inputs into the NN tooptimize these parameters to obtain the most favorable results.

In another embodiment, the heart sounds are denoised using six-stagewavelet decomposition, thresholding, and then reconstruction. Threefeature extraction techniques were used: the Decimation method, and thewavelet method. Classification of the heart diseases is done usingHidden Markov Models (HMMs).

In yet another embodiment, a wavelet transform is applied to a window oftwo periods of heart sounds. Two analyses are realized for the signalsin the window: segmentation of first and second heart sounds, and theextraction of the features. After segmentation, feature vectors areformed by using the wavelet detail coefficients at the sixthdecomposition level. The best feature elements are analyzed by usingdynamic programming.

In another embodiment, the wavelet decomposition and reconstructionmethod extract features from the heart sound recordings. An artificialneural network classification method classifies the heart sound signalsinto physiological and pathological murmurs. The heart sounds aresegmented into four parts: the first heart sound, the systolic period,the second heart sound, and the diastolic period. The following featurescan be extracted and used in the classification algorithm: a) Peakintensity, peak timing, and the duration of the first heart sound b) theduration of the second heart sound c) peak intensity of the aorticcomponent of S2(A2) and the pulmonic component of S2 (P2), the splittinginterval and the reverse flag of A2 and P2, and the timing of A2 d) theduration, the three largest frequency components of the systolic signaland the shape of the envelope of systolic murmur e) the duration thethree largest frequency components of the diastolic signal and the shapeof the envelope of the diastolic murmur.

In one embodiment, the time intervals between the ECG R-waves aredetected using an envelope detection process. The intervals between Rand T waves are also determined. The Fourier transform is applied to thesound to detect S1 and S2. To expedite processing, the system appliesFourier transform to detect S1 in the interval 0.1-0.5 R-R. The systemlooks for S2 the intervals R-T and 0.6 R-R. S2 has an aortic componentA2 and a pulmonary component P2. The interval between these twocomponents and its changes with respiration has clinical significance.A2 sound occurs before P2, and the intensity of each component dependson the closing pressure and hence A2 is louder than P2. The third heardsound S3 results from the sudden halt in the movement of the ventriclein response to filling in early diastole after the AV valves and isnormally observed in children and young adults. The fourth heart soundS4 is caused by the sudden halt of the ventricle in response to fillingin presystole due to atrial contraction.

In yet another embodiment, the S2 is identified and a normalizedsplitting interval between A2 and P2 is determined. If there is nooverlap, A2 and P2 are determined from the heart sound. When overlapexists between A2 and P2, the sound is dechirped for identification andextraction of A2 and P2 from S2. The A2-P2 splitting interval (SI) iscalculated by computing the cross-correlation function between A2 and P2and measuring the time of occurrence of its maximum amplitude. SI isthen normalized (NSI) for heart rate as follows: NSI=SI/cardiac cycletime. The duration of the cardiac cycle can be the average interval ofQRS waves of the ECG. It could also be estimated by computing the meaninterval between a series of consecutive S1 and S2 from the heart sounddata. A non linear regressive analysis maps the relationship between thenormalized NSI and PAP. A mapping process such as a curve-fittingprocedure determines the curve that provides the best fit with thepatient data. Once the mathematical relationship is determined, NSI canbe used to provide an accurate quantitative estimate of the systolic andmean PAP relatively independent of heart rate and systemic arterialpressure.

In another embodiment, the first heart sound (S1) is detected using atime-delayed neural network (TDNN). The network consists of a singlehidden layer, with time-delayed links connecting the hidden units to thetime-frequency energy coefficients of a Morlet wavelet decomposition ofthe input phonocardiogram (PCG) signal. The neural network operates on a200 msec sliding window with each time-delay hidden unit spanning 100msec of wavelet data.

In yet another embodiment, a local signal analysis is used with aclassifier to detect, characterize, and interpret sounds correspondingto symptoms important for cardiac diagnosis. The system detects aplurality of different heart conditions. Heart sounds are automaticallysegmented into a segment of a single heart beat cycle. Each segment arethen transformed using 7 level wavelet decomposition, based on Coifman4th order wavelet kernel. The resulting vectors 4096 values, are reducedto 256 element feature vectors, this simplified the neural network andreduced noise.

In another embodiment, feature vectors are formed by using the waveletdetail and approximation coefficients at the second and sixthdecomposition levels. The classification (decision making) is performedin 4 steps: segmentation of the first and second heart sounds,normalization process, feature extraction, and classification by theartificial neural network.

In another embodiment using decision trees, the system distinguishes (1)the Aortic Stenosis (AS) from the Mitral Regurgitation (MR) and (2) theOpening Snap (OS), the Second Heart Sound Split (A2_P2) and the ThirdHeart Sound (S3). The heart sound signals are processed to detect thefirst and second heart sounds in the following steps: a) waveletdecomposition, b) calculation of normalized average Shannon Energy, c) amorphological transform action that amplifies the sharp peaks andattenuates the broad ones d) a method that selects and recovers thepeaks corresponding to S1 and S2 and rejects others e) algorithm thatdetermines the boundaries of S1 and S2 in each heart cycle f) a methodthat distinguishes S1 from S2.

In one embodiment, once the heart sound signal has been digitized andcaptured into the memory, the digitized heart sound signal isparameterized into acoustic features by a feature extractor. The outputof the feature extractor is delivered to a sound recognizer. The featureextractor can include the short time energy, the zero crossing rates,the level crossing rates, the filter-bank spectrum, the linearpredictive coding (LPC), and the fractal method of analysis. Inaddition, vector quantization may be utilized in combination with anyrepresentation techniques. Further, one skilled in the art may use anauditory signal-processing model in place of the spectral models toenhance the system's robustness to noise and reverberation.

In one embodiment of the feature extractor, the digitized heart soundsignal series s(n) is put through a low-order filter, typically afirst-order finite impulse response filter, to spectrally flatten thesignal and to make the signal less susceptible to finite precisioneffects encountered later in the signal processing. The signal ispre-emphasized preferably using a fixed pre-emphasis network, orpreemphasizer. The signal can also be passed through a slowly adaptivepre-emphasizer. The preemphasized heart sound signal is next presentedto a frame blocker to be blocked into frames of N samples with adjacentframes being separated by M samples. In one implementation, frame 1contains the first 400 samples. The frame 2 also contains 400 samples,but begins at the 300th sample and continues until the 700th sample.Because the adjacent frames overlap, the resulting LPC spectral analysiswill be correlated from frame to frame. Each frame is windowed tominimize signal discontinuities at the beginning and end of each frame.The windower tapers the signal to zero at the beginning and end of eachframe. Preferably, the window used for the autocorrelation method of LPCis the Hamming window. A noise canceller operates in conjunction withthe autocorrelator to minimize noise. Noise in the heart sound patternis estimated during quiet periods, and the temporally stationary noisesources are damped by means of spectral subtraction, where theautocorrelation of a clean heart sound signal is obtained by subtractingthe autocorrelation of noise from that of corrupted heart sound. In thenoise cancellation unit, if the energy of the current frame exceeds areference threshold level, the heart is generating sound and theautocorrelation of coefficients representing noise is not updated.However, if the energy of the current frame is below the referencethreshold level, the effect of noise on the correlation coefficients issubtracted off in the spectral domain. The result is half-wave rectifiedwith proper threshold setting and then converted to the desiredautocorrelation coefficients. The output of the autocorrelator and thenoise canceller are presented to one or more parameterization units,including an LPC parameter unit, an FFT parameter unit, an auditorymodel parameter unit, a fractal parameter unit, or a wavelet parameterunit, among others. The LPC parameter is then converted into cepstralcoefficients. The cepstral coefficients are the coefficients of theFourier transform representation of the log magnitude spectrum. A filterbank spectral analysis, which uses the short-time Fourier transformation(STFT) may also be used alone or in conjunction with other parameterblocks. FFT is well known in the art of digital signal processing. Sucha transform converts a time domain signal, measured as amplitude overtime, into a frequency domain spectrum, which expresses the frequencycontent of the time domain signal as a number of different frequencybands. The FFT thus produces a vector of values corresponding to theenergy amplitude in each of the frequency bands. The FFT converts theenergy amplitude values into a logarithmic value which reducessubsequent computation since the logarithmic values are more simple toperform calculations on than the longer linear energy amplitude valuesproduced by the FFT, while representing the same dynamic range. Ways forimproving logarithmic conversions are well known in the art, one of thesimplest being use of a look-up table. In addition, the FFT modifies itsoutput to simplify computations based on the amplitude of a given frame.This modification is made by deriving an average value of the logarithmsof the amplitudes for all bands. This average value is then subtractedfrom each of a predetermined group of logarithms, representative of apredetermined group of frequencies. The predetermined group consists ofthe logarithmic values, representing each of the frequency bands. Thus,utterances are converted from acoustic data to a sequence of vectors ofk dimensions, each sequence of vectors identified as an acoustic frame,each frame represents a portion of the utterance. Alternatively,auditory modeling parameter unit can be used alone or in conjunctionwith others to improve the parameterization of heart sound signals innoisy and reverberant environments. In this approach, the filteringsection may be represented by a plurality of filters equally spaced on alog-frequency scale from 0 Hz to about 3000 Hz and having a prescribedresponse corresponding to the cochlea. The nerve fiber firing mechanismis simulated by a multilevel crossing detector at the output of eachcochlear filter. The ensemble of the multilevel crossing intervalscorresponding to the firing activity at the auditory nerve fiber-array.The interval between each successive pair of same direction, eitherpositive or negative going, crossings of each predetermined soundintensity level is determined and a count of the inverse of theseinterspike intervals of the multilevel detectors for each spectralportion is stored as a function of frequency. The resulting histogram ofthe ensemble of inverse interspike intervals forms a spectral patternthat is representative of the spectral distribution of the auditoryneural response to the input sound and is relatively insensitive tonoise The use of a plurality of logarithmically related sound intensitylevels accounts for the intensity of the input signal in a particularfrequency range. Thus, a signal of a particular frequency having highintensity peaks results in a much larger count for that frequency than alow intensity signal of the same frequency. The multiple levelhistograms of the type described herein readily indicate the intensitylevels of the nerve firing spectral distribution and cancel noiseeffects in the individual intensity level histograms. Alternatively, thefractal parameter block can further be used alone or in conjunction withothers to represent spectral information. Fractals have the property ofself similarity as the spatial scale is changed over many orders ofmagnitude. A fractal function includes both the basic form inherent in ashape and the statistical or random properties of the replacement ofthat shape in space. As is known in the art, a fractal generator employsmathematical operations known as local affine transformations. Thesetransformations are employed in the process of encoding digital datarepresenting spectral data. The encoded output constitutes a “fractaltransform” of the spectral data and consists of coefficients of theaffine transformations. Different fractal transforms correspond todifferent images or sounds.

Alternatively, a wavelet parameterization block can be used alone or inconjunction with others to generate the parameters. Like the FFT, thediscrete wavelet transform (DWT) can be viewed as a rotation in functionspace, from the input space, or time domain, to a different domain. TheDWT consists of applying a wavelet coefficient matrix hierarchically,first to the full data vector of length N, then to a smooth vector oflength N/2, then to the smooth-smooth vector of length N/4, and so on.Most of the usefulness of wavelets rests on the fact that wavelettransforms can usefully be severely truncated, or turned into sparseexpansions. In the DWT parameterization block, the wavelet transform ofthe heart sound signal is performed. The wavelet coefficients areallocated in a non-uniform, optimized manner. In general, large waveletcoefficients are quantized accurately, while small coefficients arequantized coarsely or even truncated completely to achieve theparameterization. Due to the sensitivity of the low-order cepstralcoefficients to the overall spectral slope and the sensitivity of thehigh-order cepstral coefficients to noise variations, the parametersgenerated may be weighted by a parameter weighing block, which is atapered window, so as to minimize these sensitivities. Next, a temporalderivator measures the dynamic changes in the spectra. Power featuresare also generated to enable the system to distinguish heart sound fromsilence.

After the feature extraction has been performed, the heart soundparameters are next assembled into a multidimensional vector and a largecollection of such feature signal vectors can be used to generate a muchsmaller set of vector quantized (VQ) feature signals by a vectorquantizer that cover the range of the larger collection. In addition toreducing the storage space, the VQ representation simplifies thecomputation for determining the similarity of spectral analysis vectorsand reduces the similarity computation to a look-up table ofsimilarities between pairs of codebook vectors. To reduce thequantization error and to increase the dynamic range and the precisionof the vector quantizer, the preferred embodiment partitions the featureparameters into separate codebooks, preferably three. In the preferredembodiment, the first, second and third codebooks correspond to thecepstral coefficients, the differenced cepstral coefficients, and thedifferenced power coefficients.

With conventional vector quantization, an input vector is represented bythe codeword closest to the input vector in terms of distortion. Inconventional set theory, an object either belongs to or does not belongto a set. This is in contrast to fuzzy sets where the membership of anobject to a set is not so clearly defined so that the object can be apart member of a set. Data are assigned to fuzzy sets based upon thedegree of membership therein, which ranges from 0 (no membership) to 1.0(full membership). A fuzzy set theory uses membership functions todetermine the fuzzy set or sets to which a particular data value belongsand its degree of membership therein.

To handle the variance of heart sound patterns of individuals over timeand to perform speaker adaptation in an automatic, self-organizingmanner, an adaptive clustering technique called hierarchical spectralclustering is used. Such speaker changes can result from temporary orpermanent changes in vocal tract characteristics or from environmentaleffects. Thus, the codebook performance is improved by collecting heartsound patterns over a long period of time to account for naturalvariations in speaker behavior. In one embodiment, data from the vectorquantizer is presented to one or more recognition models, including anHMM model, a dynamic time warping model, a neural network, a fuzzylogic, or a template matcher, among others. These models may be usedsingly or in combination.

In dynamic processing, at the time of recognition, dynamic programmingslides, or expands and contracts, an operating region, or window,relative to the frames of heart sound so as to align those frames withthe node models of each S1-S4 pattern to find a relatively optimal timealignment between those frames and those nodes. The dynamic processingin effect calculates the probability that a given sequence of framesmatches a given word model as a function of how well each such framematches the node model with which it has been time-aligned. The wordmodel which has the highest probability score is selected ascorresponding to the heart sound.

Dynamic programming obtains a relatively optimal time alignment betweenthe heart sound to be recognized and the nodes of each word model, whichcompensates for the unavoidable differences in speaking rates whichoccur in different utterances of the same word. In addition, sincedynamic programming scores words as a function of the fit between wordmodels and the heart sound over many frames, it usually gives thecorrect word the best score, even if the word has been slightlymisspoken or obscured by background sound. This is important, becausehumans often mispronounce words either by deleting or mispronouncingproper sounds, or by inserting sounds which do not belong.

In dynamic time warping (DTW), the input heart sound A, defined as thesampled time values A=a(1) . . . a(n), and the vocabulary candidate B,defined as the sampled time values B=b(1) . . . b(n), are matched up tominimize the discrepancy in each matched pair of samples. Computing thewarping function can be viewed as the process of finding the minimumcost path from the beginning to the end of the words, where the cost isa function of the discrepancy between the corresponding points of thetwo words to be compared. Dynamic programming considers all possiblepoints within the permitted domain for each value of i. Because the bestpath from the current point to the next point is independent of whathappens beyond that point. Thus, the total cost of [i(k), j(k)] is thecost of the point itself plus the cost of the minimum path to it.Preferably, the values of the predecessors can be kept in an M×N array,and the accumulated cost kept in a 2.times.N array to contain theaccumulated costs of the immediately preceding column and the currentcolumn. However, this method requires significant computing resources.For the heart sound recognizer to find the optimal time alignmentbetween a sequence of frames and a sequence of node models, it mustcompare most frames against a plurality of node models. One method ofreducing the amount of computation required for dynamic programming isto use pruning. Pruning terminates the dynamic programming of a givenportion of heart sound against a given word model if the partialprobability score for that comparison drops below a given threshold.This greatly reduces computation, since the dynamic programming of agiven portion of heart sound against most words produces poor dynamicprogramming scores rather quickly, enabling most words to be prunedafter only a small percent of their comparison has been performed. Toreduce the computations involved, one embodiment limits the search tothat within a legal path of the warping.

A Hidden Markov model can be used in one embodiment to evaluate theprobability of occurrence of a sequence of observations O(1), O(2), . .. O(t), . . . , O(T), where each observation O(t) may be either adiscrete symbol under the VQ approach or a continuous vector. Thesequence of observations may be modeled as a probabilistic function ofan underlying Markov chain having state transitions that are notdirectly observable. The transitions between states are represented by atransition matrix A=[a(i,j)]. Each a(i,j) term of the transition matrixis the probability of making a transition to state j given that themodel is in state i. The output symbol probability of the model isrepresented by a set of functions B=[b(j)(O(t)], where the b(j)(O(t)term of the output symbol matrix is the probability of outputtingobservation O(t), given that the model is in state j. The first state isalways constrained to be the initial state for the first time frame ofthe utterance, as only a prescribed set of left-to-right statetransitions are possible. A predetermined final state is defined fromwhich transitions to other states cannot occur. Transitions arerestricted to reentry of a state or entry to one of the next two states.Such transitions are defined in the model as transition probabilities.For example, a heart sound pattern currently having a frame of featuresignals in state 2 has a probability of reentering state 2 of a(2,2), aprobability a(2,3) of entering state 3 and a probability ofa(2,4)=1−a(2, 1)−a(2,2) of entering state 4. The probability a(2, 1) ofentering state 1 or the probability a(2,5) of entering state 5 is zeroand the sum of the probabilities a(2,1) through a(2,5) is one. Althoughthe preferred embodiment restricts the flow graphs to the present stateor to the next two states, one skilled in the art can build an HMM modelwithout any transition restrictions.

The Markov model is formed for a reference pattern from a plurality ofsequences of training patterns and the output symbol probabilities aremultivariate Gaussian function probability densities. The heart soundtraverses through the feature extractor. During learning, the resultingfeature vector series is processed by a parameter estimator, whoseoutput is provided to the hidden Markov model. The hidden Markov modelis used to derive a set of reference pattern templates, each templaterepresentative of an identified S1-S4 pattern in a vocabulary set ofreference patterns. The Markov model reference templates are nextutilized to classify a sequence of observations into one of thereference patterns based on the probability of generating theobservations from each Markov model reference pattern template. Duringrecognition, the unknown pattern can then be identified as the referencepattern with the highest probability in the likelihood calculator.

In one embodiment, a wireless monitoring system includes one or morewireless nodes communicating over aeronautical mobile telemetryfrequency; and a wearable appliance in communication with the one ormore wireless nodes, the appliance monitoring one or more vital signs.

In addition to hospital patient and equipment monitoring, the system canbe used in other applications. In an employee access application, thesystem enables an employer to selectively grant access to specific roomsof a facility. Additionally, when an employee is in an area where he isnot normally present, the system can flag a warning to the facilityadministrator. Further, the computer of the employee can be accesslocked so that only the employee with the proper wireless authorizationcan work on a particular computer. All employee accesses, physical aswell as electronic, are tracked for regulatory requirements such asHIPAA requirements so that the administrator knows that only authorizedpersonnel are present. Additionally, the employee can be paged in casehe or she is needed through the voice walkie-talkie over the Zigbeenetwork.

In a vending machine monitoring application, the system can monitorvending machines remotely located to a central monitoring system. Forexample, transmitters can be placed within soda machines to monitor thedepletion of soda machines. When a “sold out” indication is present inthe vending machine, the system can transmit refill/reorder requests toa supplier using the wireless network or the POTS network. Also, thestatus of the vending machine can be monitored (e.g., the temperature ofa ice cream machine or soda machine) to notify a supplier or themaintenance department when maintenance is required.

In a prisoner monitoring embodiment, people who are subject toincarceration need to be monitored. The system can constantly monitorthe prisoners to ensure they are present. A prisoner has a wirelessappliance that is secured or unremovably attached to his person. If thewireless appliance is forcibly removed it immediately transmits anotification to the prisoner monitor. In a Home Confinement Monitoringembodiment, a convict can be required not to leave their home. They aremonitored by the wireless appliance attached to the “home prisoners”which are then monitored by a central monitoring center or station whichcan be a sheriffs office. In the home prisoner monitoring system, thewireless appliance is secured to or unremovably attached to the homeprisoner and if they move outside of the range of the network (i.e., theleave the house), no transmission will be received by the wirelesstransceiver and an alarm is issued by the remote home prisoner monitor.In one embodiment, the alarm can be a phone call or an email message orfax message to the monitoring center or station.

In an Animal Monitoring embodiment, the system can monitor the statusand presence of animals in a stock yard or on a farm by the similarmethodologies discussed above. In this embodiment a plurality of animalscan be monitored for presence as well as condition. For example, thesystem can ensure that animals have not wandered off as well asdetermine conditions such as temperature or heart rate of an animal,this can be accomplished by placing a wireless appliance on the animal.

In a utility monitoring embodiment, a wireless appliance is interfacedwith a utility meter and thereafter transmits the current meter readingat predetermined intervals. Because of the low power requirements ofZigbee and the low duty cycle and low data rate required fortransmitting the information, the battery for powering the Zigbee radiotransmitter can last many months or more.

“Computer readable media” can be any available media that can beaccessed by client/server devices. By way of example, and notlimitation, computer readable media may comprise computer storage mediaand communication media. Computer storage media includes volatile andnonvolatile, removable and non-removable media implemented in any methodor technology for storage of information such as computer readableinstructions, data structures, program modules or other data. Computerstorage media includes, but is not limited to, RAM, ROM, EEPROM, flashmemory or other memory technology, CD-ROM, digital versatile disks (DVD)or other optical storage, magnetic cassettes, magnetic tape, magneticdisk storage or other magnetic storage devices, or any other mediumwhich can be used to store the desired information and which can beaccessed by client/server devices. Communication media typicallyembodies computer readable instructions, data structures, programmodules or other data in a modulated data signal such as a carrier waveor other transport mechanism and includes any information deliverymedia.

All references including patent applications and publications citedherein are incorporated herein by reference in their entirety and forall purposes to the same extent as if each individual publication orpatent or patent application was specifically and individually indicatedto be incorporated by reference in its entirety for all purposes. Manymodifications and variations of this invention can be made withoutdeparting from its spirit and scope, as will be apparent to thoseskilled in the art. The specific embodiments described herein areoffered by way of example only. The above specification, examples anddata provide a complete description of the manufacture and use of thecomposition of the invention. Since many embodiments of the inventioncan be made without departing from the spirit and scope of theinvention, the invention resides in the claims hereinafter appended.

While this invention has been particularly shown and described withreferences to preferred embodiments thereof, it will be understood bythose skilled in the art that various changes in form and details may bemade therein without departing from the spirit and scope of theinvention as defined by the appended claims.

What is claimed is:
 1. A monitoring system, comprising: one or morewireless nodes communicating over an aeronautical mobile telemetry (AMT)band from about 2360 to 2400 MHz; and an appliance in communication withthe one or more wireless nodes to capture a patient vital sign.
 2. Thesystem of claim 1, comprising patient monitoring equipment coupled tothe wireless nodes to display patient vital signs without attachingcables to a patient.
 3. The system of claim 1, wherein the applianceincludes a high reliability transmission link with a redundantcommunication protocol to transmit patient data.
 4. The system of claim1, comprising a set of wireless nodes restricted to indoor uses and aset of wireless nodes without location restriction.
 5. The system ofclaim 1, wherein wireless nodes have predetermined quality of service,coexistence with other wireless devices, data integrity and security. 6.The system of claim 1, wherein the wireless nodes comprise adaptivespectrum aware wireless nodes.
 7. The system of claim 1, wherein theappliance is implanted inside a patient.
 8. The system of claim 1,comprising a wireless coordinator coupled to the wireless nodes.
 9. Thesystem of claim 1, comprising a call center coupled to the appliance toprovide a human response.
 10. The system of claim 1, comprising adatabase to store medicine taking habits, eating and drinking habits,sleeping habits, or exercise habits.
 11. The system of claim 1,comprising hospital or operating room patient monitoring equipmentcoupled to the wireless node.
 12. The system of claim 1, wherein theappliance comprises a sensor to capture at least one of: RR (respiratoryrate), SpO2 (oxygen saturation), ECG (electrocardiogram), HR (heartrate), core temperature (inside heart) and peripheral temperature (ontop of instep), CI (cardiac output index), systematic pressure,systematic systolic arterial pressure; systematic diastolic arterialpressure; systematic mean arterial pressure, CVP (central venouspressure), pulmonary pressures, pulmonary systolic arterial pressure,pulmonary diastolic arterial pressure, pulmonary mean arterial pressure,svO2 (oxygen saturation in the lung artery), ETCO2 (outcoming carbondioxide), FIO (ingoing oxygen), diuretics, patient weight, patient fluidbalance (ingoing and outcoming fluids), EEG, intracranial pressure(ICP).
 13. The system of claim 1, wherein the wireless nodes are in anambulance, comprising a long range transceiver coupled to the wirelessnodes to send patient data from the ambulance to the hospital.
 14. Thesystem of claim 1, comprising a cellular transceiver, opticaltransceiver, or body area network coupled to the wireless nodes.
 15. Thesystem of claim 1, comprising a plurality of directional antennas placedaround the patient or under a patient, wherein each directional antennais aimed at the appliance to capture transmission from the wearableappliance.
 16. A wireless system for a patient, comprising: an appliancemonitoring clinical information from the patient and communicating usingan aeronautical mobile telemetry (AMT) band between about 2360 to 2400MHz.
 17. The system of claim 16, comprising a master transmitter or hubcontrolling the transmissions of the appliance, where in the hubaggregate patient data and transmit clinical information for viewing bya healthcare professional.
 18. The system of claim 16, wherein applianceis used for self-management of diabetes, wound healing, hypertension, orheart failure.
 19. The system of claim 16, wherein the appliancecommunicates with a receiver either in the patient's pocket or in ahospital room.
 20. The system of claim 16, wherein the appliance isoutside a hospital, the information aggregated locally from at least onesensor coupled to the appliance is relayed into a cellular network toprovide doctors or hospitals with patient monitoring.
 21. The system ofclaim 16, comprising a processor with analytical software to process theclinical information and determine medical patterns in the data.
 22. Thesystem of claim 16, wherein the appliance is made by a firstmanufacturer, comprising a second appliance made by a secondmanufacturer coupled to the one or more wireless nodes, wherein the twoappliances are interoperable, or wherein the two appliances arecompatible, or wherein the two appliances communicate withoutinterference from each other.
 23. The system of claim 16, wherein theappliance is made by a first manufacturer, comprising a second appliancemade by a second manufacturer coupled to the one or more wireless nodes,wherein the two appliances do not interfere with each other's wirelesscommunication.
 24. The system of claim 16, wherein the applianceminimizes electrical cable on the patient for ECG, EKG, EEG, or vitalsign monitoring.
 25. A wireless system for a patient, comprising: anappliance monitoring clinical information from the patient andcommunicating with an aeronautical mobile telemetry (AMT) band fromabout 2360 to 2400 MHz, wherein the clinical information is aggregatedfor local processing and forwarded to one or more centralized displaysand electronic medical records.
 26. The system of claim 25, comprisingan accelerometer.
 27. The system of claim 25, wherein the appliancecomprises a sensor to capture at least one of: RR (respiratory rate),SpO2 (oxygen saturation), ECG (electrocardiogram), HR (heart rate), coretemperature (inside heart) and peripheral temperature (on top ofinstep), CI (cardiac output index), systematic pressure, systematicsystolic arterial pressure; systematic diastolic arterial pressure;systematic mean arterial pressure, CVP (central venous pressure),pulmonary pressures, pulmonary systolic arterial pressure, pulmonarydiastolic arterial pressure, pulmonary mean arterial pressure, svO2(oxygen saturation in the lung artery), ETCO2 (outcoming carbondioxide), FIO (ingoing oxygen), diuretics, patient weight, patient fluidbalance (ingoing and outcoming fluids), EEG, intracranial pressure(ICP).